Capacity constraint Research Papers - Academia.edu (original) (raw)

This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach.

- by and +1
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- Production Planning, Genetic Algorithm, Raw materials, Soft Drinks

Growth and liberalization of world trade have increased the risks of introduction of quarantine plant pests into importing countries. Import inspection of incoming commodities is a major tool for prevention of pest introductions related to world trade, but inspection capacities are limited. This article develops a theoretical and an empirical model for the optimal allocation of inspection effort for phytosanitary inspection of imported commodities when the inspecting agency has a limited capacity. It is shown that the optimal allocation of inspection effort equalizes marginal costs of pest introduction across risky commodity pathways. The numerical illustration finds the optimal allocation of inspection effort of chrysanthemum cuttings imported in the Netherlands. The numerical results suggest that ceteris paribus, greater inspection effort should be allocated to pathways whose inspection yields a greater reduction in the expected costs of pest introduction. The numerical results also suggest that import inspection has a high marginal benefit. In particular, we found that each additional euro of the inspection capacity decreases the expected costs of pest introduction from 18 to 49 euros, depending on the initial inspection capacity.

- by Olaf van Kooten
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- Agricultural Economics, Applied Economics, Empirical Model, Capacity constraint

In this paper, we consider a newsvendor problem commonly encountered in retail stores that cater to budget-sensitive shoppers. The newsvendor sells multiple products, and in addition to determining order quantities must also determine the selling price of each product sold. The demand for each product is of a stochastic nature and depends on the demands of other products, i.e., is cross-elastic. We transform the objective function into a form that is amenable to developing integer-programming solutions and then develop a numeric optimization procedure rooted in the Nelder-Mead search technique. We obtain encouraging numerical results on some small-scale and large-scale problems. To the best of our knowledge, this is the first work that produces implementable solutions for a scenario that is particularly relevant to retailers catering to budget-sensitive customers who are abundant in the current economy.

- by A. Gosavi
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- Multidisciplinary, Production economics, Numerical Optimization, Price Setting

This paper investigates the capability of Sweep Algorithm in solving the vehicle routing problem for public transport The Sweep Algorithm is firstly introduced as a method to search shortest route in the vehicle routing problem. In order to evaluate the result of the algorithm, current routes profile of a public transport is presented. An application is constructed based on the algorithm and tested using current routes data. The route generation is performed repeatedly using different constraints in order to obtain the optimal solution. A route is selected based on shortest distance and capacity constraint. Each constraint affects the route selection to gain different combination of routes. Revenue and operational cost are considered to select the best combination of routes. Two methods in sweep algorithm are implemented and compared to find the better method. The result shows that Sweep Algorithm is capable of solving vehicle routing problem for public transport under certain constraints.

- by Roberto Calvo
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- Applied Mathematics, Local Search, Natural disaster, Metaheuristic
- by Andrea Seraghiti and +1
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- Routing, Routing algorithm, Energy Harvesting, Resource Limitation

R ewarding customers with own products or services has become an increasingly popular practice across a spectrum of industries such as airlines, hotels, and telecommunication. In these service industries, firms face demand uncertainty and strict short-term capacity constraint. When the market demand is low, firms hold excess capacities that would lead to intense price competition. In this paper we study the adoption and design of reward programs in the context of capacity management. We demonstrate that it is optimal for firms to offer capacity rewards when the market demand varies from one period to the other. By offering the reward programs, firms can effectively reduce available capacities when the market demand is low, and hence credibly show their unwillingness to undersell. Such a commitment can encourage their competitors to set their prices high. When firms provide reward programs, if a firm sets a higher price than the other and sells less today, in the future the firm can benefit from the other firm's larger reduction in available capacity through rewards. Thus, reward programs also provide additional incentives for firms to set higher current prices. Finally, since reward programs can add flexibility in adjusting the available capacities to the market demand, firms increase the size of regular capacities with reward programs.

- by mengze shi
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- Management Science, Price Competition, Service industry, Spectrum
- by Gilles Goncalves
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- Genetic Algorithms, Stochastic Programming, Routing, Transportation

In this paper, we consider a multicommodity flow problem where for each pair of vertices, (u,v), we are required to sendf half-units of commodity (uv) from u to v and f half-units of commodity (vu) from v to u without violating capacity constraints. Our main result is an algorithm for performing th9 task provided that the capacity of each cut exceeds the demand across the cut by a b(log n) factor. The condition on cuts is required in the worst case, and is trivially within a i(log n) factor of optimal for any flow problem.

- by Frank Leighton
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- Algorithms, Queueing theory, Network Flows, DISTRIBUTION

In high-demand bus networks, limited-stop services promise benefits for both users and operators, and have proven their attractiveness in systems such as Transmilenio (Bogota, Colombia) and Transantiago (Santiago, Chile). The design of these services involves defining their itinerary, frequency and vehicle size, yet despite the importance of these factors for the network's efficiency, no published works appear to provide the tools for designing high-frequency unscheduled services on an urban bus corridor, minimizing social costs.

- by Ricardo Giesen and +1
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- Applied Mathematics, Services, Modeling, Sensitivity Analysis
- by Samik Ghosh
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- Distributed Computing, Wireless Mesh Networks, Mobile Communication, Mesh Networks

The predicted increase of air-traffic poses a significant capacity problem at the United States major airports, which have current capacity limitations. To accommodate for this, the Closely Spaced Parallel Approach (CSPA) operation has been proposed as a viable solution for the future demands of the year 2020. As part of efforts to understand the capacity constraints on the Terminal Area, several factors are to be examined closely if capacity gain of two folds is expected. CSPA operations allows for such capacity gain, however, it requires construction of additional runways, meeting the Wake Vortex separation standards by an alternative approach to the existing in-trail separation and analysis on enabling Communication, Navigation and Surveillance (CNS) technologies that ensure safe CSPA operations. The student design team at George Mason University is working with the Raytheon Company on the Terminal Area Capacity Enhancement Concept (TACEC) design and will complete its work in May 04.

- by Marshall Gangel
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- United States, Capacity constraint

The resource-constrained production planning problem in semicontinuous multiproduct food industries is addressed. In particular, the case of yogurt production, a representative food process, in a real-life dairy facility is studied in detail. The problem in question is mainly focused on the packing stage, whereas timing and capacity constraints are imposed with respect to the batch stage to ensure the generation of feasible production plans. A novel mixed discrete/continuous-time mixed-integer linear programming model, based on the definition of families of products, is proposed. Timing and sequencing decisions are taken for product families rather than for products; thus, reducing significantly the model size. Additionally, material balances are realized for every particular product, permitting the detailed optimization of inventory and operating costs. Packing units operate in parallel and share resources. Qualitative as well as quantitative objectives are considered. Several industrial case studies, including also some unexpected events scenarios, have been solved to optimality.

- by Luis Puigjaner
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- Mechanical Engineering, Chemical Engineering, Production Planning, Food Processing

This paper proposes an enhanced measure of accessibility that explicitly considers circumstances in which the capacity of the transport infrastructure is limited. Under these circumstances, passengers may suffer longer waiting times, resulting in the
delay or cancellation of trips. Without considering capacity constraints, the standard measure overestimates the accessibility contribution of transport infrastructure. We estimate the expected waiting time and the probability of forgoing trips based on the M/GB/1 type of queuing and discrete-event simulation, and formally incorporate the impacts of capacity constraints into a new measure: capacity constrained accessibility (CCA). To
illustrate the differences between CCA and standard measures of accessibility, this paper estimates the accessibility change in the Beijing–Tianjin corridor due to the Beijing–Tianjin intercity high-speed railway (BTIHSR). We simulate and compare the CCA and
standard measures in five queuing scenarios with varying demand patterns and service headway assumptions. The results show that (1) under low system loads condition, CCA is compatible with and absorbs the standard measure as a special case; (2) when demand
increases and approaches capacity, CCA declines significantly; in two quasi-real scenarios, the standard measure overestimates the accessibility improvement by 14–30 % relative to the CCA; and (3) under the scenario with very high demand and an unreliable timetable, the CCA is almost reduced to the pre-BTIHSR level. Because the new CCA measure effectively incorporates the impact of capacity constraints, it is responsive to different arrival rules, service distributions, and system loads, and therefore provides a more realistic representation of accessibility change than the standard measure.

- by Yu Shen and +1
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- Accessibility, High-speed rail, Capacity constraint

We study the Student-Project Allocation problem (SPA), a generalisation of the classical Hospitals / Residents problem (HR). An instance of SPA involves a set of students, projects and lecturers. Each project is offered by a unique lecturer, and both projects and lecturers have capacity constraints. Students have preferences over projects, whilst lecturers have preferences over students. We present an optimal lineartime algorithm for allocating students to projects, subject to these preferences and capacities. In particular, the algorithm finds a stable matching of students to projects. Here, the concept of stability generalises the stability definition in the HR context. The stable matching produced by our algorithm is simultaneously best-possible for all students. The SPA problem model that we consider is very general and has applications to a range of different contexts besides student-project allocation.

- by Robert Irving and +1
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- Student Project, Linear-time algorithm, Capacity constraint

The general aim of this paper is to discuss the apparently irreconcilable tensions that exist between policies for air transport liberalization in the European Union (EU), those directed at environmental sustainability, and the inadequacy of plans for additional airport capacity and modal shift to meet projected growth in air transport. The paper analyses the contradictory responses of the major stakeholders in the air transport industry to these problems, concentrating in particular on the environmentally incompatible strategies adopted by airlines in the competitive market-place. It concludes that environmentally driven capacity constraints at airports will eectively determine air transport's development within the EU, and that current laissez-faire attitudes of airlines and their regulators are unlikely to prevail as 'polluter pays' principles are more ®rmly implemented. Ó

Vendor managed inventory is an integrated approach for retailer-vendor coordination, according to which the vendor decides on the appropriate inventory levels within bounds that are agreed upon in a contractual agreement between vendor and retailers. In this contract, the vendor usually incurs a penalty cost for items exceeding these bounds. The purpose of this paper is to develop a model for a supply chain with single vendor and multiple retailers under VMI mode of operation. This model explicitly includes the VMI contractual agreement between the vendor and retailers. The developed model can easily describe supply chains with capacity constraints by selecting high penalty cost. Theorems are established to alleviate the complexity of the model and render the mathematics tractable. Moreover, an efficient algorithm is devised to find the global optimal solution. This algorithm reduces the computational efforts significantly. In addition, numerical experiments are conducted to show the utility of the proposed model.

Recently, it has been recognized that revenue management of cruise ships is different from that of airlines or hotels. Among the main differences is the presence of multiple capacity constraints in cruise ships, i.e., the number of cabins in different categories and the number of lifeboat seats, versus a single constraint in airlines and hotels (i.e., number of seats or rooms). We develop a discrete-time dynamic capacity control model for a cruise ship characterized by multiple constraints on cabin and lifeboat capacities. Customers (families) arrive sequentially according to a stochastic process and request one cabin of a certain category and one or more lifeboat seats. The cruise ship revenue manager decides which requests to accept based on the remaining cabin and lifeboat capacities at the time of an arrival as well as the type of the arrival. We show that the opportunity cost of accepting a customer is not always monotone in the reservation levels or time. This non-monotone behavior implies that ''conventional" booking limits or critical time periods capacity control policies are not optimal. We provide analysis and insights justifying the non-monotone behavior in our cruise ship context. In the absence of monotonicity, and with the optimal solution requiring heavy storage for ''large" (industry-size) problems, we develop several heuristics and thoroughly test their performance, via simulation, against the optimal solution, well-crafted upper bounds, and a first-come first-served lower bound. Our heuristics are based on rolling-up the multidimensional state space into one or two dimensions and solving the resulting dynamic program (DP). This is a strength of our approach since our DP-based heuristics are easy to understand, solve and analyze. We find that single-dimensional heuristics based on decoupling the cabins and lifeboat problems perform quite well in most cases.

- by Mark Nagel
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- Seasonality, San Francisco, Major League Baseball, Capacity constraint

Strategy identifies two primary sets of processes through which the firm creates value for its customers by moving goods and information through marketing channels: demand-focused and supply-focused processes. Historically, firms have invested resources to develop a core differential advantage in one or other of these areas-but rarely in both-often resulting in mismatches between demand (what customers want) and supply (what is available in the marketplace). This paper suggests that successfully managing the supply chain to create customer value requires extensive integration between demandfocused processes and supply-focused processes that is based on a foundation of value creation through intraorganizational knowledge management. Integrating demand and supply processes helps firms prioritize and ensure fulfillment based upon the shared generation, dissemination, interpretation and application of real-time customer demand as well as ongoing supply capacity constraints. We draw upon literature in marketing, logistics, supply chain man-agement and strategy to introduce a conceptual framework of demand and supply integration (DSI). We also offer insights for managerial practice and an agenda for future research in the relatively under-researched, but strategically important, area of demand and supply integration.

- by Daniel J . Flint and +1
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- Marketing, Knowledge Management, Supply Chain Management, Supply Chain

This paper investigates the impact of freezing the master production schedule (MPS) in multi-item single-level systems with a single resource constraint under demand uncertainty. It also examines the impact of environmental factors on the selection of MPS freezing parameters. A computer model is built to simulate master production scheduling activities in a multi-item system under a rolling time horizon. The result of the study shows that the parameters for freezing the MPS have a significant impact on total cost, schedule instability and the service level of the system. Furthermore, the selection of freezing parameters is also significantly influenced by some environmental factors such as capacity tightness and cost structure. While some findings concerning the performance of MPS freezing parameters without capacity constraints can be generalised to the case of limited capacity, other conclusions under capacity constraints are different from those without capacity constraints. r 2002 Published by Elsevier Science B.V.

- by Jinxing Xie and +1
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- Multidisciplinary, Production economics, Computer Simulation, Computer Model

The Vehicle Routing Problem (VRP) is one of the most well studied problems in operations research, both in real life problems and for scientific research purposes. During the last 50 years a number of different formulations have been proposed, together with an even greater number of algorithms for the solution of the problem. In this paper, the VRP is formulated as a problem of two decision levels. In the first level, the decision maker assigns customers to the vehicles checking the feasibility of the constructed routes (vehicle capacity constraints) and without taking into account the sequence by which the vehicles will visit the customers. In the second level, the decision maker finds the optimal routes of these assignments. The decision maker of the first level, once the cost of each routing has been calculated in the second level, estimates which assignment is the better one to choose. Based on this formulation, a bilevel genetic algorithm is proposed. In the first level of the proposed algorithm, a genetic algorithm is used for calculating the population of the most promising assignments of customers to vehicles. In the second level of the proposed algorithm, a Traveling Salesman Problem (TSP) is solved, independently for each member of the population and for each assignment to vehicles. The algorithm was tested on two sets of benchmark instances and gave very satisfactory results. In both sets of instances the average quality is less than 1%. More specifically in the set with the 14 classic instances proposed by Christofides, the quality is 0.479% and in the second set with the 20 large scale vehicle routing problems, the quality is 0.826%. The algorithm is ranked in the tenth place among the 36 most known and effective 556 J Glob Optim (2007) 38:555-580 algorithms in the literature for the first set of instances and in the sixth place among the 16 algorithms for the second set of instances. The computational time of the algorithm is decreased significantly compared to other heuristic and metaheuristic algorithms due to the fact that the Expanding Neighborhood Search Strategy is used.

- by Panos M Pardalos
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- Applied Mathematics, Operations Research, Genetic Algorithm, Global Optimization

Scheme irrigation management information system (SIMIS) is a decision support system for managing irrigation schemes. It can be used either as a management tool or as a training tool. The data needed for the technical and administrative management of the scheme can be stored, edited and displayed in various forms. They can then be used for helping in water management, calculating irrigation requirements, developing irrigation layouts, scheduling water deliveries, and keeping records of water consumption. The SIMIS approach is based on simple water balance models with capacity constraints. The user can simulate management alternatives, assess the results and try out new alternatives, until a satisfactory solution is found. SIMIS also helps in the administrative aspects of managing irrigation schemes (accounting, calculating water charges, controlling maintenance activities) and in assessing their performance. #

A decision support system (DSS) integrated in a geographical information system (GIS) for the analysis and evaluation of different transport policies is presented. The objective of the tool is to assist transport administrators enhance the efficiency of the transportation supply while improving environmental and energy indicators. The DDS works on three levels. The first performs the transport network analysis, the second assesses the energy consumption and pollutant emissions and the third evaluates the several policies selected. Road traffic is simulated using a deterministic, multi-modal traffic assignment model with capacity constraints. The model allows the estimation of traffic flow patterns within each link of the road network starting from the knowledge of the network characteristics and traffic demand. Energy consumption and pollutant emission calculations are based on the methodology developed by the CORINAIR working group. The evaluation of each policy scenario is based on a number of traffic, environmental and energy indicators. A multi-criteria analysis, where decision is based upon judging over appropriate weighted criteria, is adopted. Models are integrated in a GIS environment, which serves as the repository of the data as well as the user interface of the tool. The use of the tool is demonstrated through characteristic case studies on the Greater Athens Area in Greece. Two policy measures, one concerning the extension of the region where half of the private cars are prohibited from entering to the Municipality of Athens and the other the reduction of parking places in the same region by 50% are evaluated.

- by Ala Daoud
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- User Interface, Energy Consumption, Multidisciplinary, Decision support system

Contents Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1... more

Contents Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 What Is Local Food? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Geography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

- by Katherine Ralston and +2
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- Food Safety, Food Policy, Local Economic Development, Life Cycle Assessment

This paper considers bidding behavior in a repeated procurement auction setting. We study highway procurement data for the state of California between December 1994 and October 1998. We consider a dynamic bidding model that takes into account the presence of intertemporal constraints such as capacity constraints. We estimate the model non-parametrically and assess the presence of dynamic constraints in bidding.

- by mireia jofre-bonet
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- Economics, European Economic Integration, Non Parametric, Capacity constraint

5 Comparison of various VRP relaxations 6 Branch-and-cut methods Separation algorithms Branching strategies 7 Branch-and-cut-and-price method R. Baldacci (DEIS) Exact Algorithms for the VRP May 12, 2008 2 / 66 Outline (2) Pricing and cut generation 8 Set partitioning with additional cuts Finding an optimal VRP solution Bounding procedure Route generation algorithm 9 Summary of the computational experiments 10 Appendix 11 References R. Baldacci (DEIS) Exact Algorithms for the VRP May 12, 2008 3 / 66 Problem description

- by Daniele Vigo
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- Applied Mathematics, Business and Management, Vehicle routing, OR

We develop a stochastic two-period production/inventory planning model, which combines the use of information updating process with the flexibility of different delivery lead-times ordering strategy. Several decision variables are used: two orders are placed at the beginning of the first and second periods respectively and received immediately; another order is placed at the beginning of the first period and received with one period delay. The two different ordering/production modes, with zero and one period delivery lead-time, have different specific costs. The model permits to the retailer to return a certain amount of the available inventory to the supplier at the beginning of each period . Furthermore, a market information permits to update, between successive time periods, the random second period demand probability distribution. Via a dynamic programming approach, we exhibit the structure of the optimal policy, which is partially characterized by threshold levels. Then, via a numerical study, we exhibit the impact of the information quality of the proposed model.

- by Yves Dallery
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- Inventory Control, Multidisciplinary, Production economics, Boolean Satisfiability

Advance selling occurs when sellers allow buyers to purchase at a time preceding consumption (Shugan and Xie 2000). Electronic tickets, smart cards, online prepayments, and other technological advances make advance selling possible for many, if not all, service providers. These technologies lower the cost of making complex transactions at a greater distance from the seller's site. They also give sellers more control over advance selling by decreasing arbitrage. As technology enhances the capability to advance sell, more academic attention is vital. This paper strives to exploit these technologies by developing advance-selling strategies.

- by Arbie Always
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- Marketing, Social Welfare, Airline Industry, Risk Aversion

- by Theodore Stank and +2
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- Marketing, Knowledge Management, Supply Chain Management, Supply Chain

In this paper, we propose a new model for the within-day Dynamic Traffic Assignment (DTA) on road networks in which we explicitly address the simulation of queue spillovers where a user equilibrium is expressed as a fixed-point problem in terms of arc flow temporal profiles, i.e., in the infinite dimension space of time's functions. The model integrates spillback congestion into an existing formulation of the DTA based on continuous-time variables and implicit path enumeration, which is capable of explicitly representing the formation and dispersion of vehicle queues on road links, but allows them to exceed the arc length. The propagation of congestion among adjacent arcs will be achieved through the introduction of time-varying exit and entry capacities that limit the inflow on downstream arcs in such a way that their storage capacities are never exceeded. Determining the temporal profile of these capacity constraints requires solving a system of spatially non-separable macroscopic flow models on the supply side of the DTA based on the theory of kinematic waves, which describe the dynamic of the spillback phenomenon and yield consistent network performances for given arc flows. We also devise a numerical solution algorithm of the proposed continuous-time formulation allowing for "long time intervals" of several minutes, and give an empirical evidence of its convergence. Finally, we carry out a thorough experimentation in order to estimate the relevance of spillback modeling in the context of the DTA, compare the proposed model in terms of effectiveness with the Cell Transmission Model, and assess the efficiency of the proposed algorithm and its applicability to real instances with large networks.

- by Guido Gentile
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- Applied Mathematics, Fixed Point Theory, ICT Integration model, Network Performance

The advantages of our EGCS are shown through extensive simulation results. We make a comparison between our EGCS and the previous one, which shows that our results are quite satisfactory and superiol:

- by Tsung-Che Chiang
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- Control system, Capacity constraint

During the 1920s the New York Stock Exchange's position as the dominant American exchange was eroding. Costs to customers, measured as bid-ask spreads, spiked when surging inflows of orders collided with the constraint created by a fixed number of brokers. The NYSE's management proposed and the membership approved a 25 percent increase in the number of seats by issuing a quarter-seat dividend to all members. An event study reveals that the aggregate value of the NYSE rose in anticipation of improved competitiveness. These expectations were justified as bid-ask spreads became less sensitive to peak volume days.

- by Eugene White and +1
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- Economic History, Applied Economics, Event Study, New York Stock Exchange

Carpooling is a transport system based on a shared use of private cars. The mobility managers of the Università Statale and Politecnico di Milano universities are interested in promoting the use of such system among their students and employees. The paper presents an ongoing project to design, implement and test PoliUniPool, a car pooling service for such universities. The main characteristics of the PoliUniPool service are the following: (1) the use of the system is restricted to employees, faculty and students of the two universities; (2) besides suggesting a matching between the users, the system provides the expected schedule for their trips; (3) in addition to the campus premises, users can selectas destination of their car pooling tripsthe main railway and subway stations, in order to encourage the most environmental friendly means; (4) users are informed immediately in case of delay or changes, to improve the reliability of the service; (5) the system estimates the costs for each user, in order to let the users know how to share them; (6) the system has some social network functionalities, e.g. drivers are able to set partial prearranged crews; and users may indicate other users they would prefer to car-pool with ("friends") or they don't want to ("I don't like him/her"). A web-based software tool has been implemented to manage the matching of the users. In order to solve the carpooling problem, we use an heuristics, based on a guided Monte Carlo method. The algorithm minimizes an objective function, subject to user time windows and car capacity constraints. The objective function is a weighted sum of different terms in order to maximize the number of served users, minimizing the total route length, and maximizing the satisfied user preferences (e.g. friends). The result is a matching between drivers and passengers, their schedules and the routes to be driven by each driver. The trial of the proposed service will start on September 2011 and will take into account how to introduce and promote the service, identifying regulation, incentives, modalities, and marketing actions.

- by Diego Ciccarelli and +3
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- Intelligent Transport System, Mobility Management, Multi objective optimization, User preferences

This paper presents a schedule-based dynamic assignment model for transit networks, which takes into account congestion through explicit vehicle capacity constraints. The core of this assignment model is the use of a joint choice model for departure times, stops and runs that defines a space-time path in which users decide to leave at a given time, to access the network at a given stop and to board a given run to reach their destination. The assignment model is defined through a dynamic process approach in which the within-day network loading procedure allocates users on each transit run according to user choice and to the residual capacity of vehicles arriving at stops. The proposed model, albeit general, is specified for frequent users, who constitute a particularly congestion-sensitive class of users. Finally, an application to a real-size test network (part of the Naples transit network in southern Italy) is illustrated in order to test the proposed approach and show the ability of the modelling framework to assess congestion effects on transit networks.

The Taxi Planning studies the aircraft routing and scheduling on the airport ground. This is a dynamic problem, which must be updated almost every time that a new aircraft enters or exits the system. Taxi Planning has been modelled using a linear multicommodity flow network model with side constraints and binary variables. The flow capacity constraints are used to represent the conflicts and competence between aircrafts using a given airport capacity. The "Branch and Bound" and "Fix and Relax" methodologies have been used. The computational tests have been run at the Madrid-Barajas airport, using actual data from the airport traffic.

- by ANGEL G MARIN
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- Mathematical Sciences, Branch and Bound, Network Model, Capacity constraint

Recently, manufacturers are taking a hybrid approach between MTS and MTO. However, most of literature research on production planning concentrates principally on MTS systems. The MTO area has not received the same degree of attention. There are only some research papers which are based on queueing network models that explicitly talk about the Lot Sizing Problem (LSP) in MTO sector. This paper presents a case study in MTO sector for which analytical model is still extremely complex up to now (multi-stage, multi-product, multi-location, multi-resource with setup, capacity constraints and stochastic demand). The objective is to determine a fixed optimal lot size for each manufacturing product type that will ensure Order Mean Flow Time (OMFT) target value for each finished product type. The adopted approach is carried out in three steps. A Discrete Event Simulation (DES) model was firstly implemented as a tool in estimating (OMFT) performance. Secondly, Design of Experiment is applied to conduct simulation experiments. Finally, a multiple-objective optimization is achieved by applying desirability optimization methodology. The study results illustrate that the LSP in MTO sector is viable and provides a prototype for further research in supply chain co-ordination.

- by Wafik Hachicha
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- Stochastic Process, Tabu Search, Response Surface Methodology, Comparative Study

Consider a supply chain involving one manufacturer and one independent retailer. The manufacturer distributes her product to the end consumer through the independent retailer as well as through her direct channel. Each of the two channels faces a stochastic demand. If one channel is out of stock, a fraction of the unsatisfied customers visit the other channel, which induces inventory competition between the channels. Under the scenario described above, will the manufacturer ever undercut the retailer's order when the capacity is infinite? What are the equilibria of the game? How does a capacity constraint affect the equilibrium outcome? What is the optimal inventory allocation strategy for the manufacturer? Using a game theoretic model we seek answers to the above questions. Both the capacitated and the infinite capacity games are considered. We establish the necessary condition for a manufacturer to undercut a retailer's order and show that a manufacturer may deny the retailer of inventory even when the capacity is ample. We show that there can be an equilibrium in the capacitated game where a manufacturer might not use the entire capacity and still deny a retailer inventory. We also show that a mild capacity constraint may make both parties better off and thereby increase the total supply chain profit. We develop a simple yet practical contract called the reverse revenue sharing contract and show that along with a fixed franchise fee this contract can coordinates our decentralized supply chain.

- by Suman Mallik
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- Game Theory, Supply Chain Management, Distributed System, Supply Chain

The paper deals with lot sizing and scheduling problem (LSSP) of a multi-site manufacturing system with capacity constraints and uncertain multi-product and multi-period demand. LSSP is solved by an hybrid model resulting from the... more

- by Giovanni Mummolo
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- Supply Chain Management, Decision Making, Operations Research, Production

Regional trade agreements (RTAs) present opportunities for controlling technical barriers to trade (TBTs). Using key principles and provisions of the WTO Agreement on TBT as a yardstick for analysis, this paper examines whether and how eight major regional integration agreements within the African region address TBT issues. It finds that TBT are not an important issue in Sub-Saharan African RTAs. Only one of the 8 agreements surveyed refers explicitly to the WTO TBT Agreement. Existing provisions for eliminating TBT-related barriers or harmonising legitimate technical regulations are formulated mostly in broad and nonprescriptive terms. The paper describes concrete steps that parties to these RTAs have taken in order to reduce technical barriers. Such initiatives have been taken at the national level but can also involve collaboration between RTAs. Country case studies show that weak TBT infrastructure remains a handicap for businesses and governments and that, with the exception of the Southern African Development Cooperation (SADC), investment by regional economic communities (RECs) in institutional infrastructure related to TBT has not been significant. The paper describes in some detail relevant activities taking place within SADC which could serve as a best-practice model for other African regional agreements. Serious capacity constraints stand in the way of African countries taking on the challenge of reducing TBT barriers. Also, low local levels of living standards favour weak product standard, and this acts as a barrier to upgrading product standards for export markets. Amending TBT coverage in African RTAs, a review of performance of enquiry points and assistance with infrastructure modernisation are among a set of measures recommended for achieving better TBT policy alignment among countries of the region.

- by Marthinus Breitenbach
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- Kenya, Regional Economics, Regional Integration, South Africa

This paper explores the models as well as solution techniques for the link capacitated traffic assignment problem (CTAP) that is capable of offering more realistic traffic assignment results. CTAP can be approximated by the uncapacitated TAP using different dual/penalty strategies. Two important and distinctive approaches in this category are studied and implemented efficiently. The inner penalty function (IPF) approach establishes a barrier on the boundary of the feasible set so that constraints are not violated in the solution process, and the augmented Lagrangian multiplier (ALM) approach combines the exterior penalty with primal-dual and Lagrangian multipliers concepts. In both implementations, a gradient projection (GP) algorithm was adopted as the uniform subproblem solver for its excellent convergence property and reoptimization capability. Numerous numerical results demonstrated through efficient implementations of either the IPF or the ALM approach that CTAP is computationally tractable even for large-scale problems. Moreover, the relative efficiency of IPF and ALM was explored and their sensitivity to different algorithmic issues was investigated.

- by Y. Nie
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- Applied Mathematics, Sensitivity Analysis, Comparative Study, Algorithm

Hedge funds have generated significant absolute returns (alpha) in the decade between 1995 and 2004. However, the level of alpha has declined substantially over this period. We investigate whether capacity constraints at the level of hedge fund strategies have been responsible for this decline. For four out of eight hedge fund strategies, capital inflows have statistically preceded negative movements in alpha, consistent with this hypothesis. We also find evidence that hedge fund fees have increased over the same period. Our results provide support for the rational model of active portfolio management.

- by Tarun Ramadorai
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- Portfolio Management, Hedge Funds, Five Factor Model, Capacity constraint

The pickup and delivery problem with time windows is the problem of serving a number of transportation requests using a limited amount of vehicles. Each request involves moving a number of goods from a pickup location to a delivery location. Our task is to construct routes that visit all locations such that corresponding pickups and deliveries are placed on the same route and such that a pickup is performed before the corresponding delivery. The routes must also satisfy time window and capacity constraints.

Synchronous Optical Network (SONET) in North America and Synchronous Digital Hierarchy (SDH) in Europe and Japan are the current transmission and multiplexing standards for high speed signals within the carrier infrastructure. The typical topology of a SONET network is a collection of rings connecting all the customer sites. We deal with a design problem in which each customer has to be assigned to exactly one ring and these rings have to be connected through a single federal ring. A capacity constraint on each ring is also imposed. The problem is to find a feasible assignment of the customers minimizing the total number of rings used. A Tabu Search method is proposed to solve the problem. The key elements are the use of a variable objective function and the strategic use of two neighborhoods. We have also implemented other techniques such as Path Relinking, eXploring Tabu Search and a Scatter Search. Extensive computational experiments have been done using two sets of benchmark instances. The performances of the proposed algorithms have also been compared with those of three multistart algorithms involving greedy methods previously proposed for the problem, and of the CPLEX solver. The computational experiments show the effectiveness of the proposed Tabu Search.

The Economic Dispatch Problem (EDP) is one of the important optimization problem in a power system. Traditionally, in EDP, the cost function for each generator has been approximately represented by a single quadratic function. The main aim of EDP is to minimize the total cost of generating real power while satisfying the equality constraints of power balance and the inequality generator capacity constraints. In this paper a New Economic Dispatch Problem Formulation (NEDPF) has been proposed to solve EDP. This new formulation is based on the reduction of the number of variables (number of generators) and elimination of the equality and inequality constraints, thus the transformation of the constrained non linear programming problem to an unconstrained one. The new unconstrained objective function, is minimized by Hooke-Jeeves' method. The NEDPF was tested for different cases (2, 3 and 6 generator units) and the results are judged satisfactory.

- by Lahouaria Benasla
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- Mathematical Programming, Power System, Non Linear Programming, Fuel