A reliability model for facility location design under imperfect information

Location selection of city logistics centers under sustainability

“…We name a few recent key works for completeness, for example, the hybrid multi-start heuristic (Resende and Werneck, 2006), second-order cone programming (Wagner et al, 2009), approximation algorithms (Huang and Li, 2008;Li, 2013), greedy heuristic and fix-and-optimize heuristic (Ghaderi and Jabalameli, 2013), Lagrangian relaxation heuristic (Nezhad et al, 2013), mixed integer linear programming model (Kratica et al, 2014), discrete variant of unconscious search (Ardjmand et al, 2014), multi-objective optimization model (Tang et al, 2013), and the weighted Dantzig-Wolfe decomposition and path-relinking combined method , which have been presented for solving an uncapacitated facility location problem. Also, some algorithms and methods have been proposed for solving the capacitated facility location problem to optimality such as the mixed integer programming formulation (Melkote and Daskin, 2001;Aros-Vera et al, 2013;Rosa et al, 2014), branch-and-price algorithm (Klose and Görtz, 2007), Lagrangian heuristic algorithm (Wu et al, 2006;Elhedhli and Merrick, 2012), kernel search heuristic (Guastaroba and Speranza, 2014), Lagrangian Heuristic and Ant Colony System (Chen and Ting, 2008), Lagrangian relaxation algorithm (Yun et al, 2014), a fix-and-optimize heuristic based on the evolutionary fire-fly algorithm (Rahmaniani and Ghaderi, 2013), hybrid Firefly-Genetic Algorithm (Rahmani and MirHassani, 2014), swarm intelligence based on sample average approximation (Aydin and Murat, 2013), modified Clarke and Wright savings heuristic algorithm , iterated tabu search heuristic (Ho, 2015), improved approximation algorithm (Aardal et al, 2015), two-stage robust models and algorithms , and the evolutionary multi-objective optimization approach (Rakas et al, 2004;Harris et al, 2014).…”

Improving supply system reliability against random disruptions: Strategic protection investment

“…Aksen and Aras (2012) propose bilevel fixed charge facility location problems to counter antagonist attacks. Yun et al (2015) propose a modeling framework for reliable supply chain network design when customers are unaware of the disruption status of a facility. Zarrinpoor et al (2017) study a location problem to design a robust hierarchical network for health service.…”

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

“…Therefore, the optimal solution can be obtained (Table 1). In supply chain literature on reliable facility location, the estimation of disruption probability is usually assumed perfectly accurate while there has very limited discussion on the misestimating disruption probability [24,31,32]. However, as mentioned above, the uncertainty in dynamic environments or misestimating the disruption probability would definitely affect the optimal solution.…”