Solving a dynamic facility location problem with partial closing and reopening

Jena, Sanjay Dominik; Cordeau, Jean‐François; Gendron, Bernard

doi:10.1016/j.cor.2015.10.011

Cited by 51 publications

(25 citation statements)

References 34 publications

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“…The MNCP results compare favorably with the results of previous researchers, who developed various heuristics to determine optimal or near-optimal capacity expansion levels for SCND problems. Previous heuristics yielding results within about one per cent of the optimal solution include those by Fong and Srinivasan (1981), Javid and Azad (2010), Melo et al (2012) and Jena et al (2016). Sadjady and Davoudpour (2012) also achieved heuristic Figure 6.…”

Section: Discussionmentioning

confidence: 80%

“…The most prevalent research seems to involve determining modular capacity levels to fully meet customer demands by applying both mathematical programs and heuristics (Shulman, 1991;Antunes and Peeters, 2001;Rajagopalan and Swaminathan, 2001;Amiri, 2006;Thanh et al, 2010;Javid and Azad, 2010;Sadjady and Davoudpour, 2012;Melo et al, 2012;Badri et al, 2013;and Jena et al, 2016). Other researchers have used only heuristics to make modular capacity decisions that fully meet customer demands, including Bean and Smith (1985), Syam (2000) and Dias et al (2008).…”

Section: Literature Reviewmentioning

confidence: 99%

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Determining nodal capacities for military distribution problems

Longhorn¹,

Muckensturm²

2019

JDAL

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Purpose This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo. Design/methodology/approach Supply chain network design, mixed integer programs, heuristics and regression are used in this paper. Findings This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements. Research limitations/implications This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads. Practical implications This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space. Originality/value This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.

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Section: Discussionmentioning

confidence: 80%

Section: Literature Reviewmentioning

confidence: 99%

Determining nodal capacities for military distribution problems

Longhorn¹,

Muckensturm²

2019

JDAL

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“…Since the classic solution algorithms for the capacitated location-allocation problem need a huge computational time, especially in large cases, it appears to be essential to propose an e cient solution approach to solving the model in large instances. On the other hand, the studies on location-allocation problems that utilize the Lagrangian relaxation-based solution method to solve the problem have presented the e ectiveness of this method in solving such problems [3,9,10,[18][19][20][21][22][23][24][25][26][27][28][29][30][31]. Herein, the Lagrangian Decomposition Algorithm (LDA) is proposed to solve the problem e ciently.…”

Section: Solution Methodsmentioning

confidence: 99%

Resilient Network Design in a Location-Allocation Problem with Multi-Level Facility Hardening

2018

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Many sources of risk a ect network elements, which may lead to network failure; thus, planners need to consider them in the network design. One of the most important strategies for disruption risk management is the static resilience. In this strategy, the network functionality is maintained after the disruption event by the prevention and hardening actions. In this paper, a resilient capacitated xed-charge location-allocation model is proposed. Both facility hardening and equipping of the network with backup facilities for disrupted elements are considered together to avoid supply network failure due to random disruption. Facilities are decided to be hardened in multiple levels before disruption events. The problem is formulated as a non-linear integer programming model; then, its equivalent linear form is presented. A Lagrangian Decomposition Algorithm (LDA) is developed to solve large-scale instances. Computational results con rm the high e cacy of the proposed solution approach, compared to classical solution approaches, in dealing with large-scale problems. Moreover, the superiority of the proposed model is con rmed in comparison to the classical models.

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“…Likewise, there are stochastic models, where decisions are made once based on uncertain knowledge of the future value of input parameters. See Dias et al (2007), Albareda-Sambola et al (2009), Wilhelm et al (2013), Correia et Melo (2015), Jena et al (2016) for recent articles related to multi-period models. For some interesting and recent stochastic models, please see Berman et Drezner (2008), Sonmez et Lim (2012), Klibi et al (2016), Marković et al (2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Proposed system for analyzing the location of preschools: a Brazilian case study

Endler

Scarpin

Steiner

2017

BJO&PM

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Early infant education and care have become priority issues in Brazil. The present article evaluates the spatial distribution of public preschools in the municipality of Curitiba, in Paraná State, Brazil. This problem is an important aspect of school administration and can relieve problems of inequality in public education, such as accessibility and availability of places. The main contribution of this article is the system it proposes for rationalizing decision-making in the education system in question. This system presents four complementary analyses, although they are independent of one another: (i) analysis of the current location of facilities; (ii) analysis of the proposed location; (iii) analysis for expanding the capacity of existing units; and (iv) analysis of the opening of new facilities. The models were generated using VB.NET © modeling language and were solved by the CPLEX © solver. The results showed that, in general, there is a need for immediate planning to increase the number of places available in public infant education in Curitiba, which is also a requirement for compliance with the goals of the National Education Plan (NEP) that is now in force nationwide.

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Solving a dynamic facility location problem with partial closing and reopening

Cited by 51 publications

References 34 publications

Determining nodal capacities for military distribution problems

Determining nodal capacities for military distribution problems

Resilient Network Design in a Location-Allocation Problem with Multi-Level Facility Hardening

Proposed system for analyzing the location of preschools: a Brazilian case study

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