Academic literature on the topic 'Facility Location Optimisation Problem'

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Journal articles on the topic "Facility Location Optimisation Problem"

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Lagos, Carolina, Broderick Crawford, Enrique Cabrera, Ricardo Soto, José-Miguel Rubio, and Fernando Paredes. "Comparing Evolutionary Strategies on a Biobjective Cultural Algorithm." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/745921.

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Evolutionary algorithms have been widely used to solve large and complex optimisation problems. Cultural algorithms (CAs) are evolutionary algorithms that have been used to solve both single and, to a less extent, multiobjective optimisation problems. In order to solve these optimisation problems, CAs make use of different strategies such as normative knowledge, historical knowledge, circumstantial knowledge, and among others. In this paper we present a comparison among CAs that make use of different evolutionary strategies; the first one implements a historical knowledge, the second one considers a circumstantial knowledge, and the third one implements a normative knowledge. These CAs are applied on a biobjective uncapacitated facility location problem (BOUFLP), the biobjective version of the well-known uncapacitated facility location problem. To the best of our knowledge, only few articles have applied evolutionary multiobjective algorithms on the BOUFLP and none of those has focused on the impact of the evolutionary strategy on the algorithm performance. Our biobjective cultural algorithm, called BOCA, obtains important improvements when compared to other well-known evolutionary biobjective optimisation algorithms such as PAES and NSGA-II. The conflicting objective functions considered in this study are cost minimisation and coverage maximisation. Solutions obtained by each algorithm are compared using a hypervolume S metric.
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Cabrera-Guerrero, Guillermo, Carolina Lagos, Carolina Castañeda, Franklin Johnson, Fernando Paredes, and Enrique Cabrera. "Parameter Tuning for Local-Search-Based Matheuristic Methods." Complexity 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/1702506.

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Algorithms that aim to solve optimisation problems by combining heuristics and mathematical programming have attracted researchers’ attention. These methods, also known as matheuristics, have been shown to perform especially well for large, complex optimisation problems that include both integer and continuous decision variables. One common strategy used by matheuristic methods to solve such optimisation problems is to divide the main optimisation problem into several subproblems. While heuristics are used to seek for promising subproblems, exact methods are used to solve them to optimality. In general, we say that both mixed integer (non)linear programming problems and combinatorial optimisation problems can be addressed using this strategy. Beside the number of parameters researchers need to adjust when using heuristic methods, additional parameters arise when using matheuristic methods. In this paper we focus on one particular parameter, which determines the size of the subproblem. We show how matheuristic performance varies as this parameter is modified. We considered a well-known NP-hard combinatorial optimisation problem, namely, the capacitated facility location problem for our experiments. Based on the obtained results, we discuss the effects of adjusting the size of subproblems that are generated when using matheuristics methods such as the one considered in this paper.
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Jin, Zhongyi, Kam K. H. Ng, Chenliang Zhang, Wei Liu, Fangni Zhang, and Gangyan Xu. "A risk-averse distributionally robust optimisation approach for drone-supported relief facility location problem." Transportation Research Part E: Logistics and Transportation Review 186 (June 2024): 103538. http://dx.doi.org/10.1016/j.tre.2024.103538.

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Jin, Zhiyang, Yang Li, Guohua Fu, Kunhao Dai, Na Qiu, Jinyi Liu, Mao Lin, and Zhennan Qin. "Capacitated Facility Location and Allocation with Uncertain Demand for Tourism Logistics: A Multiobjective Optimisation Approach." Mathematical Problems in Engineering 2019 (June 23, 2019): 1–18. http://dx.doi.org/10.1155/2019/4158940.

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The paper develops a Multiobjective Optimisation (MOO) model for addressing Capacitated Facility Location Problem (CFLP) in tourism logistics, where two objectives are total of cost and customer service level. Nondominated Sorting Genetic Algorithm II (NSGA II) is used to solve the model. The illustrative case with imaginary data demonstrates that the model can figure out the location of the nodes of tourism logistics network and allocation of these sites, while the total of cost is reduced by up to 56.75% and customer service level is increased by an average of 105%. The distinction of this study compared to the current papers is that our model incorporates both items A and B to the subject matter of tourism logistics, where items A refer to tourism-related products and items B involve personal goods of tourists. The model established is limited with one assumption and one limitation which are associated with Vehicle Routing Problem (VRP) and the boundary of tourism logistics activity. Therefore, further research for the elimination of these limits is recommended.
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Ou-Yang, Chao, Taufiq Budi Hanyata, and T. M. A. Ari Samadhi. "Hybrid self-adaptive-velocity particle swarm optimisation-Cooper heuristic for the facility location allocation problem in Jakarta." International Journal of Systems Science: Operations & Logistics 3, no. 2 (April 14, 2015): 63–78. http://dx.doi.org/10.1080/23302674.2015.1029565.

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Lagos, Carolina, Guillermo Guerrero, Enrique Cabrera, Stefanie Niklander, Franklin Johnson, Fernando Paredes, and Jorge Vega. "A Matheuristic Approach Combining Local Search and Mathematical Programming." Scientific Programming 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/1506084.

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A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.
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Anastasiadis, Eleftherios, Panagiotis Angeloudis, Daniel Ainalis, Qiming Ye, Pei-Yuan Hsu, Renos Karamanis, Jose Escribano Macias, and Marc Stettler. "On the Selection of Charging Facility Locations for EV-Based Ride-Hailing Services: A Computational Case Study." Sustainability 13, no. 1 (December 26, 2020): 168. http://dx.doi.org/10.3390/su13010168.

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The uptake of Electric Vehicles (EVs) is rapidly changing the landscape of urban mobility services. Transportation Network Companies (TNCs) have been following this trend by increasing the number of EVs in their fleets. Recently, major TNCs have explored the prospect of establishing privately owned charging facilities that will enable faster and more economic charging. Given the scale and complexity of TNC operations, such decisions need to consider both the requirements of TNCs and local planning regulations. Therefore, an optimisation approach is presented to model the placement of CSs with the objective of minimising the empty time travelled to the nearest CS for recharging as well as the installation cost. An agent based simulation model has been set in the area of Chicago to derive the recharging spots of the TNC vehicles, and in turn derive the charging demand. A mathematical formulation for the resulting optimisation problem is provided alongside a genetic algorithm that can produce solutions for large problem instances. Our results refer to a representative set of the total data for Chicago and indicate that nearly 180 CSs need to be installed to handle the demand of a TNC fleet of 3000 vehicles.
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Merkisz-Guranowska, Agnieszka. "A comparative study on end-of-life vehicles network design." Archives of Transport 54, no. 2 (June 30, 2020): 107–23. http://dx.doi.org/10.5604/01.3001.0014.2971.

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This paper investigates the current research in the field of the end-of-life vehicles (ELV) recycling network. The optimisation of the location of a network facilities in forward logistics in the automotive industry has received a lot of attention for many years but the reverse logistics for ELVs has been a subject of investigations since the beginning of 21st century. ELV recycling network design gained in popularity after the European Union and other countries like Japan, South Korea and recently China introduced legal obligations to organize a collecting or recycling network for used vehicles. When regulations are introduced, there is a need for a systemic solution to the problem, especially since the obligation to create a collection network is often accompanied by requirements related to its accessibility for vehicle owners or efficiency of operation. With the growing scope of legal regulations, companies or organisations responsible for the network are forced to redesign the existing recycling infrastructure in a given area so that it meets specific requirements. Initially, the most important criterion was network availability. Currently, the same importance is attached to economic, environmental and social aspects in order to meet the sustainability criteria. In this paper, forty one peer-reviewed published studies focused on network design were classified. Its main purpose is to provide an extensive review of state-of-the-art research published in the period 2000-2019. The scope of the review is limited to network design problems including facility location and flow allocation problems. Only papers that present mathematical models are considered. Studies on the ELV network design are classified based on: type of supply chain, type of network, optimisation problem, type of facilities, modelling technique, single/multi objectivity, objective function, period of time, solution approach and scope of implementation. The final part of the paper includes discussion of the methodology of the reviewed studies and some recommendations for future research area.
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Jolai, Fariborz, Reza Tavakkoli-Moghaddam, and Mohammad Taghipour. "A multi-objective particle swarm optimisation algorithm for unequal sized dynamic facility layout problem with pickup/drop-off locations." International Journal of Production Research 50, no. 15 (August 2012): 4279–93. http://dx.doi.org/10.1080/00207543.2011.613863.

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Liu, Zhao, Fang Wang, Pengcheng Xue, and Feng Xue. "Using multi-layer nested network to optimise spatial structure of tourism development between urban and rural areas based on population mobility." Indoor and Built Environment 31, no. 4 (March 1, 2022): 1028–46. http://dx.doi.org/10.1177/1420326x211054809.

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Under the bidirectional flow pattern of urban and rural factors, the tourism industry has become an important way to promote the vitality of urban and rural areas because of rural gentrification and city migration. By constructing a ‘node-link-setting’ networked land use model, this paper maps the tourism flow and geographic space networks, proposes a multi-layer nested network theory with spatial relevance from the mobility perspective to solve practical problems, such as urban–rural dual opposition and functional segmentation. We studied the high-precision mobile smart phone signalling data combined geographical data of Yichang, analysed the dynamic change process and comprehensive development mode characteristics of tourism attractions in 92 villages and towns through the social network analysis, compared tourism flow network changes in Yichang over time to construct a tourism flow network of Yichang, analysed the level and location of tourism nodes in the network and classified the tourist destinations to reveal the spatial-temporal evolution process and change the rule of the tourism flow network. The differences were compared by constructing traffic geography and infrastructure networks. The purpose is to propose guidance countermeasures for regional village unit tourism facility construction and industrial development and to maintain the integrity of spatial correlation and structural optimisation.
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Dissertations / Theses on the topic "Facility Location Optimisation Problem"

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Venables, Harry. "Ant colony optimisation : a proposed solution framework for the capacitated facility location problem." Thesis, University of Sunderland, 2011. http://sure.sunderland.ac.uk/4061/.

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This thesis is a critical investigation into the development, application and evaluation of ant colony optimisation metaheuristics, with a view to solving a class of capacitated facility location problems. The study is comprised of three phases. The first sets the scene and motivation for research, which includes; key concepts of ant colony optimisation, a review of published academic materials and a research philosophy which provides a justification for a deductive empirical mode of study. This phase reveals that published results for existing facility location metaheuristics are often ambiguous or incomplete and there is no clear evidence of a dominant method. This clearly represents a gap in the current knowledge base and provides a rationale for a study that will contribute to existing knowledge, by determining if ant colony optimisation is a suitable solution technique for solving capacitated facility location problems. The second phase is concerned with the research, development and application of a variety of ant colony optimisation algorithms. Solution methods presented include combinations of approximate and exact techniques. The study identifies a previously untried ant hybrid scheme, which incorporates an exact method within it, as the most promising of techniques that were tested. Also a novel local search initialisation which relies on memory is presented. These hybridisations successfully solve all of the capacitated facility location test problems available in the OR-Library. The third phase of this study conducts an extensive series of run-time analyses, to determine the prowess of the derived ant colony optimisation algorithms against a contemporary cross-entropy technique. This type of analysis for measuring metaheuristic performance for the capacitated facility location problem is not evident within published materials. Analyses of empirical run-time distributions reveal that ant colony optimisation is superior to its contemporary opponent. All three phases of this thesis provide their own individual contributions to existing knowledge bases: the production of a series of run-time distributions will be a valuable resource for future researchers; results demonstrate that hybridisation of metaheuristics with exact solution methods is an area not to be ignored; the hybrid methods employed in this study ten years ago would have been impractical or infeasible; ant colony optimisation is shown to be a very flexible metaheuristic that can easily be adapted to solving mixed integer problems using hybridisation techniques.
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Durán, Mateluna Cristian. "Exact solution methods for large-scale discrete p-facility location problems." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAE001.

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Cette thèse porte sur la solution exacte des problèmes NP-difficiles du p-median et du p-centre, des problèmes d'optimisation combinatoire qui deviennent rapidement difficiles à résoudre lorsque la taille de l'instance augmente. Ces problèmes de localisation discrète consistent à ouvrir un nombre défini p d'installations, puis à leur affecter un ensemble de clients selon une fonction objectif à minimiser.Tout d'abord, nous étudions le problème du p-median qui cherche à minimiser la somme des distances entre les clients et les installations ouvertes auxquelles ils sont affectés. Nous développons un algorithme basé sur la décomposition de Benders qui surpasse les méthodes exactes de l'état de l'art. L'algorithme considère une approche en deux étapes et ainsi qu'un algorithme efficace pour la séparation des coupes de Benders. Cette méthode est évaluée sur plus de 230 instances de benchmark avec jusqu'à 238025 clients et sites. De nombreuses instances sont résolues à l'optimalité pour la première fois ou ont leur meilleure solution connue améliorée.Deuxièmement, nous explorons le problème du p-centre qui cherche à minimiser la plus grande distance entre un client et l'installation ouverte qui en est la plus proche. Nous comparons d'abord les cinq principales formulations MILP de la littérature. Nous étudions la décomposition de Benders et nous proposons également un algorithme exact basé sur une procédure de partionnement des clients reposant sur la structure du problème. Toutes les méthodes proposées sont comparées à l'état de l'art dans des instances de benchmark. Les résultats obtenus sont analysés, mettant en évidence les avantages et les inconvénients de chaque méthode.Enfin, nous étudions un problème robuste du p-centre en deux étapes avec une incertitude sur les demandes et les distances des nœuds. Nous introduisons la reformulation robuste du problème basée sur les cinq principales formulations déterministes MILP de la littérature. Nous prouvons que seul un sous-ensemble fini de scénarios de l'ensemble d'incertitude infini peut être pris en compte sans perdre l'optimalité. Nous proposons également un algorithme de génération de colonnes et de contraintes et ainsi qu'un algorithme de branch-and-cut pour résoudre efficacement ce problème. Nous montrons comment ces algorithmes peuvent également être adaptés pour résoudre le problème robuste d'une seule étape. Les différentes formulations proposées sont testées sur des instances générées aléatoirement et sur un cas d'étude de la littérature
This thesis focuses on the exact solution of the NP-hard problems p-median and p-center, combinatorial optimization problems that quickly become difficult to solve as the instance size increases. These discrete location problems involve opening a defined number p of facilities and then allocating to them a set of clients according to an objective function to be minimized.First, we study the p-median problem, which seeks to minimize the sum of distances between clients and the open facilities to which they are allocated. We develop an algorithm based on Benders decomposition that outperforms state-of-the-art exact methods. The algorithm considers a two-stage approach and an efficient algorithm for separating Benders cuts. The method has been evaluated on over 230 benchmark instances with up to 238025 clients and sites. Many instances are solved to optimality for the first time or have their best known solution improved.Secondly, we explore the p-center problem, which seeks to minimize the largest distance between a client and its nearest open facility. We first compare the five main MILP formulations in the literature. We study the Benders decomposition and also propose an exact algorithm based on a client clustering procedure based on the structure of the problem. All the proposed methods are compared with the state-of-the-art on benchmark instances. The results obtained are analyzed, highlighting the advantages and disadvantages of each method.Finally, we study a robust two-stage p-center problem with uncertainty on node demands and distances. We introduce the robust reformulation of the problem based on the five main deterministic MILP formulations in the literature. We prove that only a finite subset of scenarios from the infinite uncertainty set can be considered without losing optimality. We also propose a column and constraint generation algorithm and a branch-and-cut algorithm to efficiently solve this problem. We show how these algorithms can also be adapted to solve the robust single-stage problem. The different proposed formulations are tested on randomly generated instances and on a case study drawn from the literature
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Meeyai, Sutthipong. "A Hybrid Approach for The Design of Facility Location and Supply Chain Network Under Supply and Demand Uncertainty: A Systematic Review." Thesis, Cranfield University, 2009. http://dspace.lib.cranfield.ac.uk/handle/1826/4673.

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In today’s extremely competitive marketplace, firms are facing the need to meet or exceed increasing customer expectations while cutting costs to stay competitive in a global market. To develop competitive advantage in this business climate, companies must make informed decisions regarding their supply chain. In recent years, supply chain networks have received increasing attention among companies. The decision makers confront the network design problem in different situations. In order to make decisions, especially in strategic supply chain management, decision makers must have a holistic view of all the components. Supply chain network design, particular facility location problems, is one of the most complex strategic decision problems in supply chain management The aim of this dissertation is to make an inquiry about the facility location problems and related issues in supply chain and logistics management, and the use of modelling approaches to solve these problems. The methodology is to construct a review protocol by forming a review panel, and developing a detailed search strategy with clear inclusion and exclusion criteria. In addition, the measurement for evaluating the quality of studies is presented with a strategy for extracting data and synthesising the methodologies. The search results show the background of the facility location problems, the importance and the basic questions of these problems. The taxonomy of facility location problems with eighteen factors is presented. The basic static and deterministic problems in facility location including the covering, centre, median and fixed charge problems are discussed. Also, the extension of facility location problems comprises of location-allocation, multi-objective, hierarchical, hub, undesirable and competitive problems. In terms of uncertainty, dynamic, stochastic and robust facility location problems are presented. Finally, strengths and weaknesses of different modelling approaches are discussed; importantly, gaps from the review process are indentified. Recommendations of future research are described; and the facility location problem to be addressed by the proposed research is shown. In addition, contributions of the proposed facility location problem are illustrated.
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Thangavelu, Balajee. "Single-Facility location problem among two-dimensional existing facility locations." Ohio University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1175283985.

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Wang, Yu Carleton University Dissertation Mathematics and Statistics. "The P-median problem and the uncapacitated facility location problem." Ottawa, 1996.

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Kotian, Siddharth R. "PLANAR k-CENTRA SINGLE-FACILITY EUCLIDEAN LOCATION PROBLEM." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1132796955.

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Romero, Montoya Alejandro. "Resilient Facility Location Problem for Supply Chain Design." Ohio University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou152631292582812.

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Oyewole, Gbeminiyi John. "A Study on Integrated Transportation and Facility Location Problem." Thesis, University of Pretoria, 2019. http://hdl.handle.net/2263/72419.

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The focus of this thesis is the development and solution of problems that simultaneously involve the planning of the location of facilities and transportation decisions from such facilities to consumers. This has been termed integrated distribution planning problems with practical application in logistics and manufacturing. In this integration, different planning horizons of short, medium and long terms are involved with the possibility of reaching sub-optimal decisions being likely when the planning horizons are considered separately. Two categories of problems were considered under the integrated distribution models. The first is referred to as the Step-Fixed Charge Location and Transportation Problem (SFCLTP). The second is termed the Fixed Charge Solid Location and Transportation Problem (FCSLTP). In these models, the facility location problem is considered to be a strategic or long term decision. The short to medium-term decisions considered are the Step-Fixed Charge Transportation Problem (SFCTP) and the Fixed Charge Solid Transportation Problem (FCSTP). Both SFCTP and FCSTP are different extensions to the classical transportation problem, requiring a trade-off between fixed and variable costs along the transportation routes to minimize total transportation costs. Linearization and subsequent local improvement search techniques were developed to solve the SFCLTP. The first search technique involved the development of a hands-on solution including a numerical example. In this solution technique, linearization was employed as the primal solution, following which structured perturbation logic was developed to improve on the initial solution. The second search technique proposed also utilized the linearization principle as a base solution in addition to some heuristics to construct transportation problems. The resulting transportation problems were solved to arrive at a competitive solution as regards effectiveness (solution value) compared to those obtainable from standard solvers such as CPLEX. The FCSLTP is formulated and solved using the CPLEX commercial optimization suite. A Lagrange Relaxation Heuristic (LRH) and a Hybrid Genetic Algorithm (GA) solution of the FCSLTP are presented as alternative solutions. Comparative studies between the FCSTP and the FCSLTP formulation are also presented. The LRH is demonstrated with a numerical example and also extended to hopefully generate improved upper bounds. The CPLEX solution generated better lower bounds and upper bound when compared with the extended LRH. However, it was observed that as problem size increased, the solution time of CPLEX increased exponentially. The FCSTP was recommended as a possible starting solution for solving the FCSLTP. This is due to a lower solution time and its feasible solution generation illustrated through experimentation. The Hybrid Genetic Algorithm (HGA) developed integrates cost relaxation, greedy heuristic and a modified stepping stone method into the GA framework to further explore the solution search space. Comparative studies were also conducted to test the performance of the HGA solution with the classical Lagrange heuristics developed and CPLEX. Results obtained suggests that the performance of HGA is competitive with that obtainable from a commercial solver such as CPLEX.
Thesis (PhD)--University of Pretoria, 2019.
Industrial and Systems Engineering
PhD
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Fors, Amanda. "The metric uncapacitated facility location problem : The problem and the approximation algorithms." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-140442.

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The main purpose of this work is to present the basics and history of the metric uncapacitated facility location problem and give an introduction to the approximation algorithm of Vazirani, that gives an approximation guarantee of 3 for the optimal solution for the problem. Furthermore, the algorithm of Vazirani is demonstrated by an easy problem that shows the technicalities of the algorithm.
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Wu, Tingying. "Models and algorithms for two-echelon capacitated facility location problem with facility size selection." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLE029.

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La localisation de sites est une des décisions stratégiques les plus importantes pour les entreprises dans le contexte de la mondialisation d'aujourd'hui. Les travaux existant dans la littérature traitant ce type de problèmes se concentrent principalement sur la détermination de l'emplacement des sites et des flux de produits provenant les sites localisés aux clients dans le but de minimiser le coût total de construction, de production et logistiques. Cependant, il est très important de bien choisir simultanément la capacité et la localisation des sites parce que la taille des sites a une grande influence sur ces coûts sur le long terme. La détermination de la location et de capacité des sites reste encore un problème ouvert.Dans cette thèse, nous étudions trois nouvelles variantes de problèmes de location de sites à deux échelons avec la sélection de taille (TECFLP). Les deux premières parties concentrent sur les TECFLPs avec sélection séparée de taille d’usines ou de dépôts. La troisième partie étudie le TECFLP avec sélection simultanée des tailles d’usines et de dépôts. Pour ces problèmes, trois modèles de programmation linéaire mixte sont proposés. Ensuite les approches basées sur la relaxation lagrangienne selon les caractéristiques de chaque problème sont développés. Pour améliorer les meilleures solutions proposées par les approches de relaxation lagrangienne, une méthode de recherche tabou, une méthode hybride de recherche tabou et à voisinage variable, une méthode hybride du recuit simulé et de la recherche tabou sont respectivement adaptées pour ces trois problèmes. Les algorithmes développés sont testés et évalués à travers 810 instances générées aléatoirement. Les résultats numériques montrent que nos méthodes sont capables de fournir des solutions de qualité avec un temps de calcul raisonnable
Facility location is one of the most important strategic decisions for firms in globalization. Previous works on facility location in the literature mainly focus on determining the locations of facilities and the flows of products from facilities to customers with the goal of minimizing the sum of facility opening costs, production and logistic costs. However, it’s very important to determine at the same time the appropriate sizes for these facilities because they greatly affects these costs on the long term. Determining facility location and size is always an open problem.In this thesis, we study three new two-echelon capacitated facility location problems (TECFLP) with facility size selection. The two first parts of the wok focus on two-echelon facility location problems with plant and depot size selection, respectively. The third part concentrates on TECFLP considering simultaneously plant and depot size selection. For these problems, three corresponding mixed integer programming models are formulated and then Lagrangean relaxation approaches according to the problems’ characteristics are developed. To further improve the best solutions obtained by the Lagrangean Relaxation approaches, a tabu search, a hybrid variable neighborhood tabu search and a hybrid simulated annealing tabu search are adapted for the three problems respectively. The developed algorithms are tested and evaluated through 810 randomly generated instances. Computational results show ours algorithms can provide high quality solutions within a reasonable computation time
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Books on the topic "Facility Location Optimisation Problem"

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Rosenfield, Donald B. The retailer facility location problem. Cambridge, Mass: Massachusetts Institute of Technology, 1985.

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Welch, Stephen Bernard. The obnoxious facility location problem. Birmingham: University of Birmingham, 1999.

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Barros, A. I. The multi-level uncapacitated facility location problem is not submodular. Brussels: European Institute for Advanced Studies in Management, 1992.

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Barros, A. I. A general model for the uncapacitated facility and depot location problem. Brussels: European Institute for Advanced Studies in Management, 1992.

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Vatsa, Amit. Multi-period facility location problem with an uncertain number of servers. Ahmedabad: Indian Institute of Management, 2014.

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Vatsa, Amit. Tabu search for multi-period facility location: Uncapacitated problem with an uncertain number of servers. Ahmedabad: Indian Institute of Management, 2014.

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Supply Chain Optimisation: Product/Process Design, Facility Location and Flow Control. Springer London, Limited, 2006.

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Dolgui, Alexandre, Oleg Zaikin, and Jerzy Soldek. Supply Chain Optimisation: Product/Process Design, Facility Location and Flow Control. Springer, 2014.

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(Editor), Alexandre Dolgui, Jerzy Soldek (Editor), and Oleg Zaikin (Editor), eds. Supply Chain Optimisation: Product/Process Design, Facility Location and Flow Control (Applied Optimization). Springer, 2004.

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Sniekers, Daphne. A stochastic facility location problem with transshipments and service constraints. 2005.

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Book chapters on the topic "Facility Location Optimisation Problem"

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Fallah, Hamed, Ali Naimi Sadigh, and Marjan Aslanzadeh. "Covering Problem." In Facility Location, 145–76. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_7.

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Biazaran, Maryam, and Bahareh SeyediNezhad. "Center Problem." In Facility Location, 193–217. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_9.

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Drezner, Zvi, Kathrin Klamroth, Anita Schöbel, and George O. Wesolowsky. "The Weber Problem." In Facility Location, 1–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56082-8_1.

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Bastani, Sara, and Narges Kazemzadeh. "Hierarchical Location Problem." In Facility Location, 219–41. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_10.

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Hekmatfar, Masoud, and Mirsaman Pishvaee. "Hub Location Problem." In Facility Location, 243–70. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_11.

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Karimifar, Mohammad Javad, Mohammad Khalighi Sikarudi, Esmaeel Moradi, and Morteza Bidkhori. "Competitive Location Problem." In Facility Location, 271–94. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_12.

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Bagherpoor, Zeinab, Shaghayegh Parhizi, Mahtab Hoseininia, Nooshin Heidari, and Reza Ghasemi Yaghin. "Warehouse Location Problem." In Facility Location, 295–314. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_13.

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Hassanzadeh, Anahita, Leyla Mohseninezhad, Ali Tirdad, Faraz Dadgostari, and Hossein Zolfagharinia. "Location-Routing Problem." In Facility Location, 395–417. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_17.

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Kaviani, Mohamadreza. "Location-Inventory Problem." In Facility Location, 451–71. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_19.

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Daneshzand, Farzaneh, and Razieh Shoeleh. "Multifacility Location Problem." In Facility Location, 69–92. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2151-2_4.

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Conference papers on the topic "Facility Location Optimisation Problem"

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Zhang, Shuaixiang, Yixuan Yang, Hao Tong, and Xin Yao. "Learning-Based Problem Reduction for Large-Scale Uncapacitated Facility Location Problems." In 2024 IEEE Congress on Evolutionary Computation (CEC), 1–8. IEEE, 2024. http://dx.doi.org/10.1109/cec60901.2024.10611785.

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Weng, Kerui. "Distance Constrained Facility Location Problem." In 2009 IITA International Conference on Services Science, Management and Engineering (SSME). IEEE, 2009. http://dx.doi.org/10.1109/ssme.2009.66.

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Ogunsemi, Akinola, John McCall, Mathias Kern, Benjamin Lacroix, David Corsar, and Gilbert Owusu. "Facility location problem and permutation flow shop scheduling problem." In GECCO '22: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3520304.3529033.

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Lam, Alexander. "Nash Welfare in the Facility Location Problem." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/680.

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Abstract:
In most facility location research, either an efficient facility placement which minimizes the total cost or a fairer placement which minimizes the maximum cost are typically proposed. To find a solution that is both fair and efficient, we propose converting the agent costs to utilities and placing the facility/ies such that the product of utilities, also known as the Nash welfare, is maximized. We ask whether the Nash welfare's well-studied balance between fairness and efficiency also applies to the facility location setting, and what agent strategic behaviour may occur under this facility placement.
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Suzuki, Atsuya, Tomoki Fukuba, and Takayuki Shiina. "The facility location problem with probabilistic constraints." In 2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS). IEEE, 2020. http://dx.doi.org/10.1109/scisisis50064.2020.9322732.

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Abbal, Khalil, Youssef Benadada, and El Amrani Mohammed. "Bi-level Multi-capacitated Facility location Problem." In 2020 5th International Conference on Logistics Operations Management (GOL). IEEE, 2020. http://dx.doi.org/10.1109/gol49479.2020.9314710.

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Xue, Zhaojie, Ying Gao, and Jingjing Yin. "Competitive facility location problem with exotic products." In 2017 4th International Conference on Industrial Engineering and Applications (ICIEA). IEEE, 2017. http://dx.doi.org/10.1109/iea.2017.7939201.

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André Rey, Tristan, and Jessen Page. "Facility location problem in thermal network design." In 2021 Building Simulation Conference. KU Leuven, 2021. http://dx.doi.org/10.26868/25222708.2021.30608.

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Castenow, Jannik, Björn Feldkord, Till Knollmann, Manuel Malatyali, and Friedhelm Meyer Auf der Heide. "The Online Multi-Commodity Facility Location Problem." In SPAA '20: 32nd ACM Symposium on Parallelism in Algorithms and Architectures. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3350755.3400281.

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Rodriguez-Verjan, Carlos, Vincent Augusto, Thierry Garaix, Xiaolan Xie, and Valerie Buthion. "Healthcare at home facility location-allocation problem." In 2012 IEEE International Conference on Automation Science and Engineering (CASE 2012). IEEE, 2012. http://dx.doi.org/10.1109/coase.2012.6386476.

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