Robust closed-loop global supply chain network design under uncertainty: the case of the medical device industry

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

“…SCA can deal with supply chain network design problems under both situations, where network design with known demand is formulated as a mixed-integer linear program Lee et al, 2010;Tiwari et al, 2012;Jindal and Sangwan, 2014) , while uncertain network design can be transformed into robust network design by using robust optimization techniques (Kibi et al, 2010;Mir Saman et al, 2011;Hasani et al, 2012;Baghaliana et al, 2013;Hasani et al, 2014). Decision variables used in SCA include continuous variables, which represent shipping quantities between locations, and binary variables that indicate whether each facility should be opened or closed.…”

Advanced cross-entropy in closed-loop supply chain planning

“…Crossentropy is one of the recently developed metaheuristics that has been utilized successfully in NPhard problems such as the Knapsack problem (Caserta et al, 2008), max cut, traveling salesman problem (Rubinstein and Kroese, 2004), vehicle routing problem (Chepuri and Homem-de-To the best of our knowledge, CE has not been utilized in the design and planning problem of CLSC/RLs. Previous attempts generally regard other types of metaheuristic algorithms such as genetic algorithm (Ko and Evans, 2007;Min et al, 2008;Soleimani et al, 2014), tabu search (Aras et al, 2008), simulated annealing (Pishvaee et al, 2010), memetic algorithm (Hasani et al, 2014), and particle swarm optimization (Chen et al, 2015;Soleimani and Kannan, 2015). Recent trends in metaheuristic algorithms show the necessity of developing such algorithms and the importance of continuing the process of elevating current solution methodologies with new advanced algorithms such as cross-entropy.…”

A mixed resilient‐efficient approach toward blood supply chain network design

“…In this regard, this study provides a multi-objective integrated resilient-efficient model to design a blood supply chain network under uncertainty. Consequently, it is necessary to adopt new policies and incorporate the resiliency concept in the design and planning process of the BSC as the capacity to survive, adjust, and enrich in the face of any unexpected change.The concept of efficiency as a basis to prevent wasting materials, effort, energy, budget, and time is another major issue in blood supply chain network design (BSCND) and planning (Hasani and Zegordi, 2015). On the other hand, to improve supply chain resilience, different resiliency measures as optimization tools are introduced and inserted into the considered network.…”

“…Therefore, any unpredictable changes such as natural disasters, wars, fire, labor strike, or equipment breakdowns (e.g., apheresis equipment) lead to a significant loss. Consequently, it is necessary to adopt new policies and incorporate the resiliency concept in the design and planning process of the BSC as the capacity to survive, adjust, and enrich in the face of any unexpected change.The concept of efficiency as a basis to prevent wasting materials, effort, energy, budget, and time is another major issue in blood supply chain network design (BSCND) and planning (Hasani and Zegordi, 2015). Data envelopment analysis (DEA) is known as a useful method for measuring efficiency.…”

“…The concept of efficiency as a basis to prevent wasting materials, effort, energy, budget, and time is another major issue in blood supply chain network design (BSCND) and planning (Hasani and Zegordi, 2015). Data envelopment analysis (DEA) is known as a useful method for measuring efficiency.…”