Metaheuristic applications on discrete facility location problems: a survey

Basu, Sumanta; Sharma, Megha; Ghosh, Pradip N.

doi:10.1007/s12597-014-0190-5

Cited by 55 publications

(19 citation statements)

References 85 publications

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“…Recent survey articles focus on applications of facility location in design of distribution systems (Klose and Drexl 2005), or supply chain management (Melo et al 2009), and a more general survey on UFL is given in Verter (2011). Approaches applied to UFL range from approximation algorithms (Li 2013, Shmoys et al 1997, over (semi-)Lagrangian relaxations (Beltran-Royo et al 2012) and metaheuristics (see, e.g., a survey in Basu et al 2015), to branch-and-bound-based algorithms in which lower bounds are calculated using dual ascent procedures (see, e.g., Letchford and Miller 2014). The state-of-the-art exact algorithm for UFL is given in Posta et al (2014): the algorithm is based on a message passing approach in which a metaheuristic calculates the upper bounds and passes the information to a branch-and-bound algorithm in which lower bounds are obtained by a Lagrangian relaxation solved using a bundle method.…”

Section: Linear Casementioning

confidence: 99%

Redesigning Benders Decomposition for Large-Scale Facility Location

2017

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T he uncapacitated facility location (UFL) problem is one of the most famous and most studied problems in the operations research literature. Given a set of potential facility locations and a set of customers, the goal is to find a subset of facility locations to open and to allocate each customer to open facilities so that the facility opening plus customer allocation costs are minimized. In our setting, for each customer the allocation cost is assumed to be a linear or separable convex quadratic function. Motivated by recent UFL applications in business analytics, we revise approaches that work on a projected decision space and hence are intrinsically more scalable for large-scale input data. Our working hypothesis is that many of the exact (decomposition) approaches that were proposed decades ago and discarded soon after need to be redesigned to take advantage of the new hardware and software technologies. To this end, we "thin out" the classical models from the literature and use (generalized) Benders cuts to replace a huge number of allocation variables by a small number of continuous variables that model the customer allocation cost directly. Our results show that Benders decomposition allows for a significant boost in the performance of a mixed-integer programming solver. We report the optimal solution of a large set of previously unsolved benchmark instances widely used in the available literature. In particular, dramatic speedups are achieved for UFL problems with separable quadratic allocation costs, which turn out to be much easier than their linear counterparts when our approach is used.

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Section: Linear Casementioning

confidence: 99%

Redesigning Benders Decomposition for Large-Scale Facility Location

2017

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“…For example, Manthey & Tijink [19] addressed the perturbation resilience by optimizing an uncapacitated discrete facility location problem. Although the discrete location model reflects reality more accurately in most cases, the researchers hold negative views on the practicality of the model in large-scale problems [20]. Most discrete location models are nondeterministic polynomial (NP) hard and suffer from excessive computational burden.…”

Section: Literature Reviewmentioning

confidence: 99%

An Improved Voronoi-Diagram-Based Algorithm for Continuous Facility Location Problem under Disruptions

Wang

2018

Sustainability

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The classical location models implicitly assume that the facilities, once built, will always operate as planned. However, some of the facilities may become unavailable from time to time due to disruptions which highlight the urgent need to effectively manage supply chain disruptions in spite of their low probability of occurrence. Therefore, it is critical to take account of disruptions when designing a resilient supply chain network so that it performs well as a whole even after an accidental disruption. In this paper, a stylized facility location problem is considered in a continuous plane which is solved through an improved Voronoi-diagram-based algorithm under disruption risks. The research problem is to minimize the total cost in normal and failure scenarios. Furthermore, the impact of misestimating the disruption probability is also investigated. The results numerically show that although the estimated disruption probability has a significant impact on the facilities configuration, it has a minor impact on the total quantity of facilities and the expected total cost. Therefore, this paper proposes that the decision-maker should moderately overestimate disruption risk based on the “pessimistic principle”. Finally, the conclusion considers managerial insights and proposes potential areas for future research.

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“…In the UWL, a subset of locations from a given set of potential locations is required for establishing warehouses so as to optimize a given function of these chosen locations while satisfying certain constraints (Basu et al, 2015;Michel and Van Hentenryck, 2004). In this section, the variables of the UWL problem are described.…”

Section: Uwl Problemmentioning

confidence: 99%

A New Hybrid Yin-Yang-Pair-Particle Swarm Optimization Algorithm for Uncapacitated Warehouse Location Problems

Heidari¹,

Kazemizade²,

Hakimpour³

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Yin-Yang-pair optimization (YYPO) is one of the latest metaheuristic algorithms (MA) proposed in 2015 that tries to inspire the philosophy of balance between conflicting concepts. Particle swarm optimizer (PSO) is one of the first population-based MA inspired by social behaviors of birds. In spite of PSO, the YYPO is not a nature inspired optimizer. It has a low complexity and starts with only two initial positions and can produce more points with regard to the dimension of target problem. Due to unique advantages of these methodologies and to mitigate the immature convergence and local optima (LO) stagnation problems in PSO, in this work, a continuous hybrid strategy based on the behaviors of PSO and YYPO is proposed to attain the suboptimal solutions of uncapacitated warehouse location (UWL) problems. This efficient hierarchical PSO-based optimizer (PSOYPO) can improve the effectiveness of PSO on spatial optimization tasks such as the family of UWL problems. The performance of the proposed PSOYPO is verified according to some UWL benchmark cases. These test cases have been used in several works to evaluate the efficacy of different MA. Then, the PSOYPO is compared to the standard PSO, genetic algorithm (GA), harmony search (HS), modified HS (OBCHS), and evolutionary simulated annealing (ESA). The experimental results demonstrate that the PSOYPO can reveal a better or competitive efficacy compared to the PSO and other MA.

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Metaheuristic applications on discrete facility location problems: a survey

Cited by 55 publications

References 85 publications

Redesigning Benders Decomposition for Large-Scale Facility Location

Redesigning Benders Decomposition for Large-Scale Facility Location

An Improved Voronoi-Diagram-Based Algorithm for Continuous Facility Location Problem under Disruptions

A New Hybrid Yin-Yang-Pair-Particle Swarm Optimization Algorithm for Uncapacitated Warehouse Location Problems

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