Integer Programming Research Papers - Academia.edu (original) (raw)

This paper examines the reduction in complexity of a product family through product design. By leveraging the commonalities among products in a family, the decision support methodology presented in the paper helps choose components and... more

This paper examines the reduction in complexity of a product family through product design. By leveraging the commonalities among products in a family, the decision support methodology presented in the paper helps choose components and suppliers that minimize the sum of design, procurement, and usage costs. The problem of integrated component and supplier selection is conceptualized and formulated as an integer‐programming model. Analysis of the model yields two properties, complete and continuous replacement, which form the basis of a heuristic procedure. Computational tests show that the heuristic provides results close to the optimal solution and can be used for selecting components and suppliers. Application of the model to an industrial problem is discussed.

The location and operation of harvest machinery, along with the design and construction of access roads, are important problems faced by forestry planners, making up about 55% of total production costs. One of the main challenges consists... more

The location and operation of harvest machinery, along with the design and construction of access roads, are important problems faced by forestry planners, making up about 55% of total production costs. One of the main challenges consists of finding a design that will minimize the cost of installation and operation of harvest machinery, road construction, and timber transport, while complying with the technical restrictions that apply to the operation of harvesting equipment and road construction. We can model the network design problem as a mixed-integer linear programming problem. This model is fed with cartographic information, provided by a geographic information system (GIS), along with technical and economic parameters determined by the planner. We developed a specialized heuristic for the problem to obtain solutions that enable harvesting economically profitable volumes at a low cost. This methodology was programmed into a computer system known as PLANEX and is being applied ...

Preventive maintenance is considered as a method to avoid unexpected failure in production machines. Unfortunately, conducting such maintenance is limited by resources availability thus likely causes tardiness. This research aims to... more

Preventive maintenance is considered as a method to avoid unexpected failure in production machines. Unfortunately, conducting such maintenance is limited by resources availability thus likely causes tardiness. This research aims to minimize total tardiness of preventive maintenance on production machines by developing a scheduling model. This scheduling model takes the availability of time and labor into account to get an optimal scheduling model that can minimize the tardiness. The model of preventive maintenance schedule is developed by using the Integer Linear Programming method. This method provides output in the form of preventive maintenance schedule through a purpose function which considers the specified constraints on the company. As the result, the developed model could propose a preventive maintenance schedule which reduces the total tardiness.

We study the two-user MIMO block fading twoway relay channel in the non-coherent setting, where neither the terminals nor the relay have transmit or receive knowledge of the channel realizations. We present a lower bound on the achievable... more

We study the two-user MIMO block fading twoway relay channel in the non-coherent setting, where neither the terminals nor the relay have transmit or receive knowledge of the channel realizations. We present a lower bound on the achievable sum-rate with decode-and-forward (DF) at the relay node. As a byproduct we present an achievable pre-log region of the DF scheme, defined as the limiting ratio of the rate region to the logarithm of the signal-to-noise ratio (SNR) as the SNR tends to infinity.

The high penetration of Renewable Energy Sources into electric networks shows new perspectives for the network’s management: among others, exploiting them as resources for network’s security in emergency situations. The paper focuses on... more

The high penetration of Renewable Energy Sources into electric networks shows new perspectives for the network’s management: among others, exploiting them as resources for network’s security in emergency situations. The paper focuses on the frequency stability of a portion of the grid when it remains islanded following a major fault. It proposes an optimization algorithm that considers the frequency reaction of the relevant components and minimizes the total costs of their shedding. The algorithm predicts the final frequency of the island and the active power profiles of the remaining generators and demands. It is formulated as a Mixed-Integer Non-Linear Programming problem and the high computation time due to a large-size problem is mitigated through a simplified linear version of the model that filters the integer variables. The algorithm is designed to operate on-line and preventively compute the optimal shedding actions to be engaged when islanding occurs. The algorithm is valid...

The selection problem of repairable components for a system is a kind of reliability optimization problem and is often treated as a single objective problem with the goal of maximizing the system reliability (or minimizing either time or... more

The selection problem of repairable components for a system is a kind of reliability optimization problem and is often treated as a single objective problem with the goal of maximizing the system reliability (or minimizing either time or cost spent on repairing the component). In the present paper, we formulated the selection problem of repairable components for a parallelseries system as a multi-objective optimization problem and have discussed two different models. In the first model, the reliability of subsystems are considered as different objectives. In second model the cost and time spent on repairing the components are considered as two different objectives. Selective maintenance operation is used to select the repairable components and a multi-objective goal programming algorithm is proposed to obtain compromise selection of repairable components for the two models under some given constraints. A numerical example is given to illustrate the procedure.

This paper studies the problem facing a firm of determining the optimal composition and pricing of multiple bundles offered in a market where they compete with other bundles. The analysis assumes that the prices and characteristics of the... more

This paper studies the problem facing a firm of determining the optimal composition and pricing of multiple bundles offered in a market where they compete with other bundles. The analysis assumes that the prices and characteristics of the competitor’s bundles are known and that the competition does not react in the short run to the firm’s decisions. Consumers are assumed to be rational and to maximize a random utility function. The problem is modeled as a mixed integer non-linear program, which by its nature is difficult to solve using traditional methods. A novel two-phase solution approach is therefore developed. The first phase derives a closed-form expression to solve the optimal pricing subproblem for the bundles assuming their composition is known, and the second phase then uses this expression to arrive at an optimal solution to the composition subproblem.

Finding an optimal solution of forest management scheduling problems with even flow constraints while addressing spatial concerns is not an easy task. Solving these combinatorial problems exactly with mixed-integer programming (MIP)... more

Finding an optimal solution of forest management scheduling problems with even flow constraints while addressing spatial concerns is not an easy task. Solving these combinatorial problems exactly with mixed-integer programming (MIP) methods may be infeasible or else involve excessive computational costs. This has prompted the use of heuristics. In this paper we analyze the performance of different implementations of the Simulated Annealing (SA) heuristic algorithm for solving three typical harvest scheduling problems. Typically SA consists of searching a better solution by changing one decision choice in each iteration. In forest planning this means that one treatment schedule in a single stand is changed in each iteration (i.e. one-opt move). We present a comparison of the performance of the typical implementation of SA with the new implementation where up to three decision choices are changed simultaneously in each iteration (i.e. treatment schedules are changed in more than one s...

This paper focuses on the problem of supplying the workstations of assembly lines with components during the production process. For that specific problem, this paper presents a Mixed Integer Linear Program (MILP) that aims at minimizing... more

This paper focuses on the problem of supplying the workstations of assembly lines with components during the production process. For that specific problem, this paper presents a Mixed Integer Linear Program (MILP) that aims at minimizing the energy consumption of the supplying strategy. More specifically, in contrast of the usual formulations that only consider component flows, this MILP handles the mass flow that are routed from one workstation to the other.

Software defined networking (SDN) and network functions virtualisation (NFV) are making networks programmable and consequently much more flexible and agile. To meet service level agreements, achieve greater utilisation of legacy networks,... more

Software defined networking (SDN) and network functions virtualisation (NFV) are making networks programmable and consequently much more flexible and agile. To meet service level agreements, achieve greater utilisation of legacy networks, faster service deployment, and reduce expenditure, telecommunications operators are deploying increasingly complex service function chains (SFCs). Notwithstanding the benefits of SFCs, increasing heterogeneity and dynamism from the cloud to the edge introduces significant SFC placement challenges, not least adding or removing network functions while maintaining availability, quality of service, and minimising cost. In this paper, an availability- and energy-aware solution based on reinforcement learning (RL) is proposed for dynamic SFC placement. Two policy-aware RL algorithms, Advantage Actor-Critic (A2C) and Proximal Policy Optimisation (PPO2), are compared using simulations of a ground truth network topology based on the Rede Nacional de Ensino ...