No abstract

The facility location problem and its related financial issues have a significant impact on the configuration of a supply chain structure (SCS). Although affording the setup cost of facilities requires a huge financial investment, a meticulous planning to recoup it has been neglected by an overwhelming majority of previous studies. To fill this gap, an economical investment plan of facilities is determined by striking a trade-off between the contribution of the stockholders' capital and the loan arrangement. In the context of a multiperiod three-echelon SCS, the model also determines the optimum location of plants and the best supply and distribution patterns. The model maximizes the fill rate and the net present value of the periodic cash flow including the sale revenues minus the mortgage payment, purchase, and transportation costs. To solve the proposed problem, a finely tuned Pareto-based nondominated sorting genetic algorithm (NSGA-II) and a multi-objective biogeography-based optimization (MOBBO) algorithm are employed. Moreover, the solution methods are equipped with the heuristic DROP approach and data envelopment analysis to expedite the convergence process and derive the most efficient solutions, respectively.The experiments indicate the adequacy of the solution methods due to the close proximity to the results of the exact branch-and-bound method via the general algebraic modeling system optimization software. Finally, the results of a case study associated with designing SCS of an emerging biofuel industry demonstrate the significant implication of the research. K E Y W O R D Sdata envelopment analysis, facility location problem, multiobjective optimization, net present value, supply chain management 520

The COVID-19 pandemic crisis has fundamentally changed the way we live and work forever. The business sector is forecasting and formulating different scenarios associated with the impact of the pandemic on its employees, customers, and suppliers. Various business retrieval models are under construction to cope with life after the COVID-19 Pandemic Crisis. However, the proposed plans and scenarios are static and cannot address the dynamic pandemic changes worldwide. They also have not considered the peripheral in-between scenarios to propel the shifting paradigm of businesses from the existing condition to the new one. Furthermore, the scenario drivers in the current studies are generally centered on the economic aspects of the pandemic with little attention to the social facets. This study aims to fill this gap by proposing scenario planning and analytics to study the impact of the Coronavirus pandemic on large-scale information technology-led Companies. The primary and peripheral scenarios are constructed based on a balanced set of business continuity and employee health drivers. Practical action plans are formulated for each scenario to devise plausible responses. Finally, a damage management framework is developed to cope with the mental disorders of the employees amid the disease.