A heuristic lagrangean algorithm for the capacitated plant location problem

Abstract:This study considers a multi-objective combined budget constrained facility location/network design problem (FL/NDP) in which the system uncertainty is considered. The most obvious practical examples of the problem are territorial designing and locating of academies, airline networks, and medical service centers. In order to assure the network reliability versus uncertainty, an efficient robust optimization approach is applied to model the proposed problem. The formulation is minimizing the total expected costs, including, transshipment costs, facility location (FL) costs, fixed cost of road/link utilization as well as minimizing the total penalties of uncovered demand nodes. Then, in order to consider of several system uncertainty, the proposed model is changed to a fuzzy robust model by suitable approaches. An efficient Sub-gradient based Lagrangian relaxation algorithm is applied. In addition, a practical example is studied. At the following, a series of experiments, including several test problems, is designed and solved to evaluate of the performance of the algorithm. The obtained results emphasize that considering of practical factors (e.g., several uncertainties, system disruptions, and customer satisfaction) in modelling of the problem can lead to significant improvement of the system yield and subsequently more efficient utilization of the established network.

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“…CFLP is one of the several kinds of FLPs that the LR approach was broadly applied for solving it (see [73,[77][78][79][80][81][82][83][84]). …”

Section: -1 General Pointsmentioning

confidence: 99%

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

2017

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“…The relaxation of this set of constraints results in the problem which corresponds to the formulation of the simple plant location problem in (17.1). Barceló and Casanovas (1984) proposed a Lagrangean heuristic to solve the problem CFLP_SSC in which the maximum number of facilities p is predefined and part of the model (using constraint m i=1 y i ≤ p ). They present 3 Lagrang-…”

Section: A Survey Of Subsequent Workmentioning

confidence: 99%

Hub Location Problems: The Location of Interacting Facilities

Kara

Taner

2011

International Series in Operations Research &Amp; Management Science

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), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. PrefaceThis book is the final result of a number of incidents that occurred to us while discussing location issues with colleagues at conferences. Frequently we attended presentations, in which the authors quoted the well-known references that helped to make the discipline what it is today. Upon further inquiry, though, it turned out that some of these colleagues had never actually read the original papers. We then discussed among ourselves which contributions could be credited with shaping the field. And, lo and behold, we found that we, too, had neglected to read some of the papers that form the foundation of our science. Whether it was laziness or other things that got in the way, it had become clear that something had to be done. Our first thought was to collect the original contributions (once we could agree on what they were) and reprint them. When discussing this possibility with a publisher, we immediately ran into a roadblock in the form of copyright. While this appeared to have stopped our enthusiastic effort dead in its tracks, we kept on collecting and reading what we considered original contributions.This went on until we met Camille Price, who suggested that, rather than reprinting the original contributions, we should invite some of the leaders in our field and ask them to describe the original contribution, explain and interpret it, and comment on the impact that it had to the field. This was, of course, an excellent idea, and the response by our colleagues to our pertinent requests was equally enthusiastic. What you hold in your hands is the result of this effort.In other words, the purpose of this book is to provide easy access to the main contributions to location theory. The book is organized as follows. The introductory chapter provides an overview of some of the many facets of location analysis. This is followed by contributions in the main three fields of inquiry: minisum, minimax, and covering problems. The next chapters are part of an ever-growing list of nonstandard location models: models including competitive components, those that locate undesirable facilities, those with probabilistic features, and those that allow interactions between facilities. The following chapters discuss solution techniques: after a discussion of exact and heuristic techniques, we devote an entire chapter to Weiszfeld's method, and another to Lagrangean techniques. The last chapters of this book deal with the spheres of influence that the facilities generate and that attract viii customers to them, an...

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“…The deterministic model typically assumes that all customer demands will be completely satisfied, and sometimes requires that each customer be served by a unique facility. This latter requirement is known as sole-sourcing, and the resulting model is called the (deterministic) capacitated facility-location problem with sole-sourcing (FLP) (Barcelo and Casanova [5]). …”

Section: A Stochastic Facility Location Problem With Sole Sourcingmentioning

confidence: 99%

Solving a class of stochastic mixed-integer programs with branch and price

Silva¹,

Wood

2006

Math. Program.

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Abstract. We begin this paper by identifying a class of stochastic mixed-integer programs that have column-oriented formulations suitable for solution by a branch-and-price algorithm (B&P). We then survey a number of examples, and use a stochastic facility-location problem (SFLP) for a detailed demonstration of the relevant modeling and solution techniques. Computational results with a scenario representation of uncertain costs, demands and capacities show that B&P can be orders of magnitude faster than solving the standard formulation by branch and bound. We also demonstrate how B&P can solve SFLP exactly -as exactly as a deterministic mixed-integer program -when demands and other parameters can be represented as certain types of independent, random variables, e.g., independent, normal random variables with integer means and variances.

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A heuristic lagrangean algorithm for the capacitated plant location problem

Cited by 131 publications

References 11 publications

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

Hub Location Problems: The Location of Interacting Facilities

Solving a class of stochastic mixed-integer programs with branch and price

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