Location Problem Research Papers - Academia.edu (original) (raw)

Many types of facility location/allocation models have been developed to find optimal spatial patterns with respect to location criteria such as: cost, time, coverage, and access. In this paper we develop and test location modeling... more

Many types of facility location/allocation models have been developed to find optimal spatial patterns with respect to location criteria such as: cost, time, coverage, and access. In this paper we develop and test location modeling formulations that utilize aspects of the data envelopment analysis (DEA) efficiency measure to find optimal and efficient facility location/allocation patterns. Solving for the DEA efficiency measure, together with location modeling objectives, provides a promising rich approach to multiobjective location problems.

Distribution centers location problem is concerned with how to select distribution centers from the potential set so that the total relevant cost is minimized. This paper mainly investigates this problem under fuzzy environment.... more

Distribution centers location problem is concerned with how to select distribution centers from the potential set so that the total relevant cost is minimized. This paper mainly investigates this problem under fuzzy environment. Consequentially, chanceconstrained programming model for the problem is designed and some properties of the model are investigated. Tabu search algorithm, genetic algorithm and fuzzy simulation algorithm are integrated to seek the approximate best solution of the model. A numerical example is also given to show the application of the algorithm.

The gradual covering location problem seeks to establish facilities on a network so as to maximize the total demand covered, allowing partial coverage. We focus on the gradual covering location problem when the demand weights associated... more

The gradual covering location problem seeks to establish facilities on a network so as to maximize the total demand covered, allowing partial coverage. We focus on the gradual covering location problem when the demand weights associated with nodes of the network are random variables whose probability distributions are unknown. Using only information on the range of these random variables, this study is aimed at finding the ''minmax regret" location that minimizes the worst-case coverage loss. We show that under some conditions, the problem is equivalent to known location problems (e.g. the minmax regret median problem). Polynomial time algorithms are developed for the problem on a general network with linear coverage decay functions.

The problem of locating hub facilities and allocating non-hub nodes to those hubs arises frequently in the design of communication networks, airline passenger fiow and parcel delivery networks. In this paper we consider uncapacitated... more

The problem of locating hub facilities and allocating non-hub nodes to those hubs arises frequently in the design of communication networks, airline passenger fiow and parcel delivery networks. In this paper we consider uncapacitated multiple and single allocation p-hub median problems. We develop new mixed O/l linear formulations with tight linear programming relaxations. The approach is tested on a well known and heavily used benchmark data set of real-world problems with resulting LP relaxations ranging from 10010 to 391 250 variables and from 2 101 to 3 1901 constraints, which proved to be difficult linear programs. Yet, this approach proved to be very effective: in almost all instances the linear programming solution was integer. In cases with fractional solutions, the integrality was achieved by adding a small partial set of integrality constraints. Therefore, we extended the range of optimally solvable instances of these NP-hard hub location problems, which have defied researchers for the last ten years. As an additional result for the single allocation case we were able to establish optimality of all heuristic solutions obtained via tabu search algorithm from a previous study. For the more difficult single allocation p-hub median problem we also used the best known heuristic solution as a guidance in adding integrality constraints. This novel linkage between optimal and heuristic solutions has a potential impact in a number of other problem settings, where efficient heuristic solutions exist and are probably, but not provably optimal.

Emergency medical service (EMS) providers continually seek ways to improve system performance particularly the response time to incidents. The demand for ambulances fluctuate throughout the week, depending on the day of week, and even the... more

Emergency medical service (EMS) providers continually seek ways to improve system performance particularly the response time to incidents. The demand for ambulances fluctuate throughout the week, depending on the day of week, and even the time of day, therefore EMS operators can improve system performance by dynamic relocation/redeployment of ambulances in response to fluctuating demand patters. The objective of the model is to determine the minimum number of ambulances and their locations for each time cluster in which significant changes in demand pattern occur while meeting coverage requirement with a predetermined reliability. The model is further enhanced by calculating ambulance specific busy probabilities and validated by a comprehensive simulation model. Computational results on experimental data sets and data from an EMS agency are provided. ᭧

Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to... more

Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to route the traffic between origin-destination pairs. In this paper we classify and survey network hub location models. We also include some recent trends on hub location and provide a synthesis of the literature. inter-hub connections; and that no direct service (between two non-hub nodes) is allowed. Although these assumptions are relaxed in some studies, this paper assumes that these three assumptions are satisfied unless otherwise stated. This paper classifies and surveys network hub location models. In network hub location problems there is a given network with n nodes on which the set of origins, destinations and potential hub locations are identified. The flow between origin-destination pairs, an attribute of interest associated with flows on links in the network (cost, time, distance, etc.) and the hub-to-hub transportation discount factor a are known.

The Weber problem consists of finding a point in R n that minimizes the weighted sum of distances from m points in R n that are not collinear. An application that motivated this problem is the optimal location of facilities in the... more

The Weber problem consists of finding a point in R n that minimizes the weighted sum of distances from m points in R n that are not collinear. An application that motivated this problem is the optimal location of facilities in the 2-dimensional case. A classical method to solve the Weber problem, proposed by Weiszfeld in 1937, is based on a fixed-point iteration.

Through observations from real life hub networks, we introduce the multimodal hub location and hub network design problem. We approach the hub location problem from a network design perspective. In addition to the location and allocation... more

Through observations from real life hub networks, we introduce the multimodal hub location and hub network design problem. We approach the hub location problem from a network design perspective. In addition to the location and allocation decisions, we also study the decision on how the hub networks with different possible transportation modes must be designed. In this multimodal hub location and hub network design problem, we jointly consider transportation costs and travel times, which are studied separately in most hub location problems presented in the literature. We allow different transportation modes between hubs and different types of service time promises between origindestination pairs while designing the hub network in the multimodal problem. We first propose a linear mixed integer programming model for this problem and then derive variants of the problem that might arise in certain applications. The models are enhanced via a set of effective valid inequalities and an efficient heuristic is developed. Computational analyses are presented on the various instances from the Turkish network and CAB data set.

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / t r e underutilized links in favor of concentrating flow on hub edges and better utilization of facilities operating there. As a result of this flow... more

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / t r e underutilized links in favor of concentrating flow on hub edges and better utilization of facilities operating there. As a result of this flow concentration, economies of scale can be exploited by using more efficient transporters on the hub links.

The p-median problem, like most location problems, is classified as N P -hard, and so, heuristic methods are usually used for solving it. The pmedian problem is a basic discrete location problem with real application that have been widely... more

The p-median problem, like most location problems, is classified as N P -hard, and so, heuristic methods are usually used for solving it. The pmedian problem is a basic discrete location problem with real application that have been widely used to test heuristics. Metaheuristics are frameworks for building heuristics. In this survey, we examine the p-median, with the aim of providing an overview on advances in solving it using recent procedures based on metaheuristic rules.

During the last decade, there has been a substantial interest in how to determine the optimal number and locations of traffic counters for origin-destination (OD) trip matrices estimation. On the contrary, the optimal allocation of plate... more

During the last decade, there has been a substantial interest in how to determine the optimal number and locations of traffic counters for origin-destination (OD) trip matrices estimation. On the contrary, the optimal allocation of plate scanning devices has received very limited attention, even though several authors have demonstrated that plate scanning (route identification) techniques are much more informative than those based on traditional link count information. This paper provides techniques for obtaining the optimal number and location of plate scanning devices for a given prior OD distribution pattern under different situations, i.e. maximum route identifiability or budget constraints. Two rules analogous to the counting location problem are developed, and several integer linear programming models fulfilling these rules are proposed. The proposed methods are finally illustrated by their application into Nguyen-Dupuis and Cuenca networks.

A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service provider. The underlying network design problem is based on a 4-index (5-index by... more

A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service provider. The underlying network design problem is based on a 4-index (5-index by considering capacity type) formulation of the hub location problem which are known for their tightness. The demand is elastic in the sense that the service provider can accept any fraction of the origin-destination demand. We then propose a primal decomposition method to solve instances of the problem to optimality. Numerical results confirm superiority of our approach in comparison with a general-purpose mixed integer programming solver.

An iterative method is proposed for the K facilities location problem. The problem is relaxed using probabilistic assignments, depending on the distances to the facilities. The probabilities, that decompose the problem into K... more

An iterative method is proposed for the K facilities location problem. The problem is relaxed using probabilistic assignments, depending on the distances to the facilities. The probabilities, that decompose the problem into K single-facility location problems, are updated at each iteration together with the facility locations. The proposed method is a natural generalization of the Weiszfeld method to several facilities.

In many multi-camera vision systems the effect of camera locations on the task-specific quality of service is ignored. Researchers in Computational Geometry have proposed elegant solutions for some sensor location problem classes.... more

In many multi-camera vision systems the effect of camera locations on the task-specific quality of service is ignored. Researchers in Computational Geometry have proposed elegant solutions for some sensor location problem classes. Unfortunately, these solutions use unrealistic assumptions about the cameras' capabilities that make these algorithms unsuitable for many real world computer vision applications. In this paper, the general camera placement problem is first defined with assumptions that are more consistent with the capabilities of real world cameras. The region to be observed by cameras may be volumetric, static or dynamic, and may include holes. A subclass of this general problem can be formulated in terms of planar regions that are typical of building floor plans. Given a floor plan to be observed, the problem is then to reliably compute a camera layout such that certain task-specific constraints are met. A solution to this problem is obtained via binary optimization over a discrete problem space. In experiments the performance of the resulting system is demonstrated with different real indoor and outdoor floor plans.

In this paper, we introduce the capacitated plant location problem (CPLP) with multiple facilities in the same site (CPLPM), a special case of the classical CPLP where several facilities can be opened in the same site. Applications of the... more

In this paper, we introduce the capacitated plant location problem (CPLP) with multiple facilities in the same site (CPLPM), a special case of the classical CPLP where several facilities can be opened in the same site. Applications of the CPLPM arise in a number of contexts, such as the location of polling stations. Although the CPLPM can be modelled and solved as a standard CPLP, this approach usually performs very poorly. In this paper we describe a novel Lagrangean relaxation and a tailored Lagrangean heuristic that overcome the drawbacks of classical procedures. These algorithms were used to solve a polling station location problem in Italy. Computational results show that the average deviation of the heuristic solution over the lower bound is less than 2%.

In order t o satisfy the client needs, his Utility should be increased by covering his Demand. The service Utility should be maximized through effective deployment of ATMs. Genetic Algorithm is one of widely used techniques to solve... more

In order t o satisfy the client needs, his Utility should be increased by covering his Demand. The service Utility should be maximized through effective deployment of ATMs. Genetic Algorithm is one of widely used techniques to solve complex optimization problems, such as Banking ATM's Location Problem. This paper proposes a novel Rank Based Genetic Algorithm using convolution for solving the Banking ATM's Location Problem (RGAC). The proposed RGAC maximizes demand Coverage Percentage with less number of ATM machines. The novel RGAC speeds up the convergence using Rank Concept, with limited number of iterations to obtain a high quality feasible solution in resonable time.

Materials that must be transported upstream in a production line along a linear track are said to backtrack. In this line, management attempts to simplify the workflow of jobs by assigning machines to appropriate locations along the line... more

Materials that must be transported upstream in a production line along a linear track are said to backtrack. In this line, management attempts to simplify the workflow of jobs by assigning machines to appropriate locations along the line to minimize backtracking. The problem of assigning M machines to M locations along a linear track to minimize the total backtracking of jobs forms a quadratic assignment problem (QAP) and is a difficult task; an optimum solution to such a problem with large M is computationally intractable. Therefore, an efficient, depth-first insertion heuristic is used here to improve the solution obtained by a construction heuristic, called multi-pass heuristic. A lower bound to assess the quality, and a measure of backtracking to assess the proximity of a configuration to a generalized flow line are developed in this paper. In addition to computational results, a simulation model is also used to assess the effect of reducing backtracking on overall system performance in a dynamic environment.

The paper deals with root location problems for two classes of univariate polynomials both of geometric origin. The first class discussed, the class of Steiner polynomial, consists of polynomials, each associated with a compact convex set... more

The paper deals with root location problems for two classes of univariate polynomials both of geometric origin. The first class discussed, the class of Steiner polynomial, consists of polynomials, each associated with a compact convex set \(V \subset {\mathbb{R}}^{n}\) . A polynomial of this class describes the volume of the set V + tB n as a function of t, where t is a positive number and B n denotes the unit ball in \({\mathbb{R}}^{n}\) . The second class, the class of Weyl polynomials, consists of polynomials, each associated with a Riemannian manifold \({\mathcal{M}}\) , where \({\mathcal{M}}\) is isometrically embedded with positive codimension in \({\mathbb{R}}^{n}\) . A Weyl polynomial describes the volume of a tubular neighborhood of its associated \({\mathcal{M}}\) as a function of the tube’s radius. These polynomials are calculated explicitly in a number of natural examples such as balls, cubes, squeezed cylinders. Furthermore, we examine how the above mentioned polynomials are related to one another and how they depend on the standard embedding of \({\mathbb{R}}^{n}\) into \({\mathbb{R}}^{m}\) for m > n. We find that in some cases the real part of any Steiner polynomial root will be negative. In certain other cases, a Steiner polynomial will have only real negative roots. In all of this cases, it can be shown that all of a Weyl polynomial’s roots are simple and, furthermore, that they lie on the imaginary axis. At the same time, in certain cases the above pattern does not hold. Erasmus Darwin, the nephew of the great scientist Charles Darwin, believed that sometimes one should perform the most unusual experiments. They usually yield no results but when they do . . . . So once he played trumpet in front of tulips for the whole day. The experiment yielded no results.

The hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between any origin-destination pair. In the extensive literature on... more

The hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between any origin-destination pair. In the extensive literature on this challenging network design problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Relaxation of this basic assumption constitutes the starting point of the present work. In this study, we provide a uniform modeling treatment to all the single allocation variants of the existing hub location problems, under the incomplete hub network design. No network structure other than connectivity is imposed on the induced hub network. Within this context, the single allocation incomplete p-hub median, the incomplete hub location with fixed costs, the incomplete hub covering, and the incomplete p-hub center network design problems are defined, and efficient mathematical formulations for these problems with Oðn 3 Þ variables are introduced. Computational analyses with these formulations are presented on the various instances of the CAB data set and on the Turkish network. j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / t r b

Covering models assume that a point is covered if it is within a certain distance from a facility and not covered beyond that distance. In gradual cover models it is assumed that a point is fully covered within a given distance from a... more

Covering models assume that a point is covered if it is within a certain distance from a facility and not covered beyond that distance. In gradual cover models it is assumed that a point is fully covered within a given distance from a facility, then cover gradually declines, and the point is not covered beyond a larger distance. Gradual cover models address the discontinuity in cover which may not be the correct approach in many situations. In the stochastic gradual cover model presented in this article it is assumed that the short and long distances employed in gradual cover models are random variables. This refinement of gradual cover models provides yet a more realistic depiction of actual behavior in many situations. The maximal cover model based on the new concept is analyzed and the single facility location cover problem in the plane is solved. Computational results illustrating the effectiveness of the solution procedures are presented.

We developed an efficient heuristic to solve a joint location–distribution–inventory model for a three layered supply chain. A firm must locate distribution centers to supply a commodity to spatially distributed retailers with stochastic... more

We developed an efficient heuristic to solve a joint location–distribution–inventory model for a three layered supply chain. A firm must locate distribution centers to supply a commodity to spatially distributed retailers with stochastic demand. The solution approach is based on Lagrangian relaxation, improved with validity constraints derived from the finite set of all possible combinations of mean demand and variance. The optimal solution’s lower bound is found through the optimal solution of the dual problem. The dual gap gives a threshold to the heuristic’s error. The heuristic was applied to 98 instances with an average error threshold of 3%.

In this paper, we concentrate on the service structure of ground-transportation based cargo delivery companies. The transient times that arise from nonsimultaneous arrivals at hubs (typically spent for unloading, loading, and sorting... more

In this paper, we concentrate on the service structure of ground-transportation based cargo delivery companies. The transient times that arise from nonsimultaneous arrivals at hubs (typically spent for unloading, loading, and sorting operations) can constitute a significant portion of the total delivery time for cargo delivery systems. The latest arrival hub location problem is a new minimax model that focuses on the minimization of the arrival time of the last item to arrive, taking into account journey times as well as the transient times at hubs. We first focus on a typical cargo delivery firm operating in Turkey to identify any additional system requirements. We observe that stopovers are essential components of a ground-based cargo delivery system. The existing formulations of the hub location problem in the literature do not allow stopovers since they assume direct connections between demand centers and hubs. In this paper, we propose a generic mathematical model, which allows stopovers for the latest arrival hub location problem. We improve the model using valid inequalities and lifting. We present computational results using CAB data and data from Turkey.

The p-center location problem is concerned with determining the location of p centers in a plane/space to serve n demand points having fixed locations. The continuous absolute pcenter location problem attempts to locate facilities... more

The p-center location problem is concerned with determining the location of p centers in a plane/space to serve n demand points having fixed locations. The continuous absolute pcenter location problem attempts to locate facilities anywhere in a space/plane with Euclidean distance. The continuous Euclidean p-center location problem seeks to locate p facilities so that the maximum Euclidean distance to a set of n demand points is minimized. A particle swarm optimization (PSO) algorithm previously advised for the solution of the absolute p-center problem on a network has been extended to solve the absolute pcenter problem on space/plan with Euclidean distance. In this paper we develop a PSO algorithm for the continuous absolute pcenter location problem to minimize the maximum Euclidean distance from each customer to his/her nearest facility, called "PSO-ED". This problem is proven to be NP-hard. We tested the proposed algorithm "PSO-ED" on a set of 2D and 3D problems and compared the results with a branch and bound algorithm. The numerical experiments show that PSO-ED algorithm can solve optimally location problems with Euclidean distance including up to 1,904,711 points.

Ερευνητικά εργαλεία, που επιτελούν διάφορους σκοπούς, έχουν δημιουργηθεί κατά καιρούς. Η ποικιλία τους είναι πάρα πολύ μεγάλη. Σκοπός της εργασίας αυτής είναι να δημιουργηθεί ένα νέο εργαλείο, μια πλατφόρμα/εφαρμογή ιστού, στην οποία ο... more

Ερευνητικά εργαλεία, που επιτελούν διάφορους σκοπούς, έχουν δημιουργηθεί κατά καιρούς. Η ποικιλία τους είναι πάρα πολύ μεγάλη. Σκοπός της εργασίας αυτής είναι να δημιουργηθεί ένα νέο εργαλείο, μια πλατφόρμα/εφαρμογή ιστού, στην οποία ο χρήστης/ερευνητής να μπορεί να εκτελεί αλγορίθμους. Στην παρούσα εργασία έχουν υλοποιηθεί αλγόριθμοι από την ερευνητική περιοχή της επιχειρησιακής έρευνας και ειδικότερα για προβλήματα χωροθέτησης μονάδων παραγωγής. Έγιναν πειραματισμοί με τους αλγόριθμους που υλοποιήθηκαν και καταγράφηκαν οι χρόνοι εκτέλεσής τους στις διαφορετικές συνθήκες εκτέλεσής τους. Η πλατφόρμα/εφαρμογή έγινε με αξιοποίηση του framework Dsphinx, το οποίο είναι σε php, χρησιμοποιήθηκαν βιβλιοθήκες python και JavaScript για την απεικόνιση των δικτύων, δημιουργήθηκαν και χρησιμοποιήθηκαν κλάσεις και συναρτήσεις για την δημιουργία δικτύων και τη μέτρηση του χρόνου εκτέλεσης των αλγορίθμων

We consider vector optimization problems on Banach spaces without convexity assumptions. Under the assumption that the objective function is locally Lipschitz we derive Lagrangian necessary conditions on the basis of Mordukhovich... more

We consider vector optimization problems on Banach spaces without convexity assumptions. Under the assumption that the objective function is locally Lipschitz we derive Lagrangian necessary conditions on the basis of Mordukhovich subdifferential and the approximate subdifferential by Ioffe using a non-convex scalarization scheme. Finally, we apply the results for deriving necessary conditions for weakly efficient solutions of nonconvex location problems.

In this paper, we propose a p-median problem with uncertain edge lengths where uncertainty is characterized by given intervals. The uncertainty in edge lengths may appear in transportation costs or travel times along the edges in any... more

In this paper, we propose a p-median problem with uncertain edge lengths where uncertainty is characterized by given intervals. The uncertainty in edge lengths may appear in transportation costs or travel times along the edges in any network location problem. Minimax regret approach is a promising tool to cope with uncertainty in network location problems. However, minimax regret algorithms normally suffer from complexity, and they are time consuming. We propose a robust optimization approach to obtain the robust linear counterpart for the same class of the nominal p-median problem. The performance of the proposed model is compared with minimax regret approach through a simple but illustrative example, and results are discussed in more details.

The multicommodity location problem with balancing requirements is related to one of the major logistics issues faced by distribution and transportation firms: the management of a fleet of vehicles over a medium to long term planning... more

The multicommodity location problem with balancing requirements is related to one of the major logistics issues faced by distribution and transportation firms: the management of a fleet of vehicles over a medium to long term planning horizon. To solve this problem, we present a branch-and-bound algorithm in which bounds are computed by a dual-ascent procedure. We particularly emphasize the design

The objective of the project we present is that of implementing and validating a decision support system for urban waste management on a regional area, to be used as a means for evaluating general policies for regional service... more

The objective of the project we present is that of implementing and validating a decision support system for urban waste management on a regional area, to be used as a means for evaluating general policies for regional service organisation and, in particular, for identifying areas suitable for locating waste treatment and disposal plants, with special reference to controlled landfill plants. The system works on a prototypical case study, which refers to an area composed of specifically selected provinces in Sicily. For the design and implementation of the system, several topics have been considered, such as the identification of a representative case study, the identification and collection of relevant information and its structuring in databases, the design of combinatorial optimisation algorithms for solving the core location problem, the study of models for evaluating the different alternatives and their framing in a complete multicriteria decision model, the choice of hardware and system software suitable for the implementation of a decision support system supporting all above mentioned activities, and, finally, the solution of the case study by means of the DSS.

Multi-Level Location Problems are generally considered as complex. To deal with these problems we propose an approach based on Holonic MultiAgent Systems (HMAS). HMAS have already proven to be a convenient way to engineer complex systems.... more

Multi-Level Location Problems are generally considered as complex. To deal with these problems we propose an approach based on Holonic MultiAgent Systems (HMAS). HMAS have already proven to be a convenient way to engineer complex systems. This approach was merged with Artificial Potential Fields (APF) mechanims. The solution is obtained simultaneously with the holarchy. The holarchy is thus used to exploit and control the emergence of the solution. This solution is then evaluated to check its relevance according to global objectives represented thanks to a fitness function. This model was efficiently applied to a multi-level distribution system.

The present paper deals with the problem of locating hubs for freight mobility in urban and suburban areas. In particular, we present a heuristic method that combines aspects coming from both classical simple plant location problems and... more

The present paper deals with the problem of locating hubs for freight mobility in urban and suburban areas. In particular, we present a heuristic method that combines aspects coming from both classical simple plant location problems and shortest path ones on multimodal graphs. In the first phase of the proposed heuristics, we identify those nodes that could be attractive poles

In this study, a mathematical model is suggested concerning the location of VHF/UHF frequency radio jammer systems to the terrain parts to conduct single frequency or sequential frequency jamming, and then a decision support system (DSS),... more

In this study, a mathematical model is suggested concerning the location of VHF/UHF frequency radio jammer systems to the terrain parts to conduct single frequency or sequential frequency jamming, and then a decision support system (DSS), based on the suggested model, is formed. Location problem is modelled by the maximum covering location problem and LINGO-8 package program is used to solve the model. Interaction with the user is provided via the MS-Excel program in the DSS. In the application part of the study, a scenario was set up and the model was run for the two cases, weighted and equally weighted situations of the targets. With the same scenario, backup positions for the jammer systems were tried to be determined and solutions for the scenario were evaluated.

This paper deals with a capacitated hub location problem arising in the design of telecommunications networks. The problem is different from the classical hub location problem in two ways: the cost of using an edge is not linear but... more

This paper deals with a capacitated hub location problem arising in the design of telecommunications networks. The problem is different from the classical hub location problem in two ways: the cost of using an edge is not linear but stepwise and the capacity of a hub restricts the amount of traffic transiting through the hub rather than the incoming traffic. In this paper both an exact and a heuristic method are presented. They are compared and combined in a heuristic concentration approach to investigate whether it is possible to improve the results within limited computational times. ᭧

During the last decade the tremendous success of mobile phone systems has triggered considerable technological advances as well as the investigation of mathematical models and optimization algorithms to support planning and management... more

During the last decade the tremendous success of mobile phone systems has triggered considerable technological advances as well as the investigation of mathematical models and optimization algorithms to support planning and management decisions. In this chapter, we give an overview of some of the most significant optimization problems arising in planning second and third generation cellular networks, we describe the main corresponding mathematical models, and we briefly mention some of the computational approaches that have been devised to tackle them. For second generation systems (GSM), the planning problem can be subdivided into two distinct subproblems: coverage planning, in which the antennas are located so as to maximize service coverage, and capacity planning, in which frequencies are assigned to the antennas so as to maximize a measure of the overall quality of the received signals. For third generation systems (UMTS) network planning is even more challenging, since, due to the peculiarities of the radio interface, coverage and capacity issues must be simultaneously addressed.

This paper deals with a Hub Location Problem arising in Telecommunication Network Design. The considered network presents two different kinds of nodes: access nodes, that represent source and destination of traffic demands but cannot be... more

This paper deals with a Hub Location Problem arising in Telecommunication Network Design. The considered network presents two different kinds of nodes: access nodes, that represent source and destination of traffic demands but cannot be directly connected, and transit nodes, that have no own traffic demand but collect traffic from access nodes and route it through the network. Transit nodes are supposed to be fully connected. Given a set of access nodes and a set of potential locations for the transit nodes, the problem is to decide number and positions of the transit nodes in order to guarantee that all access nodes are allocated to a transit node, satisfying capacity constraints. The goal is to minimize the total cost of the network, which is the sum of connection costs and nodes fixed costs. The problem is a Hub Location Problem, which is known to be NP-hard. A local search approach is proposed and different metaheuristic algorithms, such as tabu search, iterated local search and random multistart, have been developed, based on such local search 1 .

of almost 800 000 circuits) prior to the hardware debugging of timing. The 3081 is characterized by a tight statistical timing design. abstract may be used without further permission in computer-based and other information-service... more

of almost 800 000 circuits) prior to the hardware debugging of timing. The 3081 is characterized by a tight statistical timing design. abstract may be used without further permission in computer-based and other information-service systems. Permission to republish other excerpts should be obtained from the Editor. ROBERT B. HITCHCOCK. SR. ET AL.

Network measurement is essential for assessing performance issues, identifying and locating problems. Two common strategies are the passive approach that attaches specific devices to links in order to monitor the traffic that passes... more

Network measurement is essential for assessing performance issues, identifying and locating problems. Two common strategies are the passive approach that attaches specific devices to links in order to monitor the traffic that passes through the network and the active approach that generates explicit control packets in the network for measurements. One of the key issues in this domain is to minimize the overhead in terms of hardware, software, maintenance cost and additional traffic.

In this paper a well-known formulation for the capacitated single-allocation hub location problem is revisited. An example is presented showing that for some instances this formulation is incomplete. The reasons for the incompleteness are... more

In this paper a well-known formulation for the capacitated single-allocation hub location problem is revisited. An example is presented showing that for some instances this formulation is incomplete. The reasons for the incompleteness are identified leading to the inclusion of an additional set of constraints. Computational experiments are performed showing that the new constraints also help to decrease the computational time required to solve the problem optimally.

We propose a collaborative e-Work based optimization approach for assisting the strategic logistic network design problem, which considers fleet design and customer clustering decisions. Normally, fleet design and customer clustering... more

We propose a collaborative e-Work based optimization approach for assisting the strategic logistic network design problem, which considers fleet design and customer clustering decisions. Normally, fleet design and customer clustering decisions are made by mid-level logistics managers while network design decision is made independently by high-level logistics managers. In the proposed approach, strategic distribution network design is modeled as a Facility Location Problem, considering long term inventory control decisions. On the other hand, tactical fleet design and customer clustering decisions are modeled based on a Hub and Spoke cost structure. An e-Work based heuristic approach is proposed to solve collaboratively the network design problem at strategic and tactical levels. The collaborative solution approach results from a particular sequential decomposition of the problem, similarly to traditional location–allocation heuristics, modeling an information sharing strategy between decision makers involved at each organizational level. A numerical application of the approach with real data based instances shows significant benefits, when compared to a non-collaborative independent optimization, where the hierarchical levels share no dynamic information and base their decisions on static and independent optimization models. These results show evidence of the advantage of the e-collaborative approach to deal with logistic decisions at different hierarchical levels, organizational units, or companies, compared to non-integrated non-linear mixed integer programming models.

Responding to true emergencies in the shortest possible time can save lives, prevent permanent injuries and reduce suffering. Most covering models consider an emergency covered if an ambulance is available within a given time or distance... more

Responding to true emergencies in the shortest possible time can save lives, prevent permanent injuries and reduce suffering. Most covering models consider an emergency covered if an ambulance is available within a given time or distance threshold. From the modeling perspective shorter or longer responses within this threshold are all tallied as covered, conversely the emergencies immediately outside the threshold are considered uncovered. However, if the shorter responses are given more weight along with the volume of such incidents, while still meeting the system wide coverage requirements, both customers and providers can benefit from reduced response times. We formulate a model to determine the locations for a given set of ambulances to minimize the system wide expected response distances while meeting coverage requirements. We solve the models with a heuristic search algorithm and present computational and comparative statistics using data from an EMS agency.

This paper describes a study aimed at evaluating the capabilities of simulated annealing in dealing with complex, real-world multi-period location problems raised by school network planning in Portugal. The problems were formulated as... more

This paper describes a study aimed at evaluating the capabilities of simulated annealing in dealing with complex, real-world multi-period location problems raised by school network planning in Portugal. The problems were formulated as mixed-integer linear optimization models. The models allow for facility closure or size reduction besides facility opening and size expansion, with sizes possibly limited to a set of pre-de®ned standards. They assume facility costs to be divided into a ®x component and two variable components, respectively dependent on facility size and facility attendance. Results obtained through the study indicate that simulated annealing can be a useful tool for solving these kinds of models. Ó

A foundation of forecasting Tropical Cyclones (TCs) is to locate their centers. There are still many difficulties in TC center locating, especially when there is an unclear eye or when spiral bands are difficult to be recognized. It is... more

A foundation of forecasting Tropical Cyclones (TCs) is to locate their centers. There are still many difficulties in TC center locating, especially when there is an unclear eye or when spiral bands are difficult to be recognized. It is usually done by hand operationally, and multiple forecasters' results may be inconsistent. In this paper, we treat the locating problem as an optimization one. An objective locating scheme is developed, using infrared (IR) satellite cloud images. A novel Spiral Band Model (SBM) is designed to extract and describe the spiral pattern of a spiral band which spirals out from a TC's center. SBM is based on a spiral band region, different from existing curvilinear models which are based on curves. A simple criterion is also defined to score the matching degree between a template derived by SBM and the spiral band of a TC. In this paper the TC center locating problem is transformed to an optimization problem, and the Chaos Immune Evolutionary Algorithm (CIEA) is employed to solve this optimization problem. The spiral center of the template found at the end of the optimization process is the estimated location of the true TC's center. The experimental result demonstrates that the proposed scheme obtains the best average error of 0.0930°in latitude/longitude in comparison with the best track data. It is well within the relative error of about 0.3°from the results of different TC warning centers. It provides objective information for forecasters to estimate TCs' centers.

This paper is focused on the problem of locating preventive health care facilities. The aim is to maximize participation to prevention programs. We assume that distance is a major determinant of participation and people would go to the... more

This paper is focused on the problem of locating preventive health care facilities. The aim is to maximize participation to prevention programs. We assume that distance is a major determinant of participation and people would go to the closest facility for preventive health care. Each facility is required to have more than a predetermined number of clients because of the direct relationship between volume and quality of preventive services. We provide a mathematical formulation and present alternative solution approaches for this new location problem. We report on computational performance of the proposed methods in locating public health centers in Fulton County, Georgia and mammography screening centers in Montreal, Quebec.