Financially embedded facility location decisions on designing a supply chain structure: A case study

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.