Sustainable supplier selection and order allocation: A novel multi-objective programming model with a hybrid solution approach - Moheb-Alizadeh, Hadi; Handfield, Robert (Computers & industrial engineering, 2019)
•Developing an innovative sustainable supplier selection and order allocation model.•Obtaining a single objective model using the ε-constraint method.•Solving the single objective model using Benders decomposition algorithm.•Improving Benders decomposition algorithm using various computational methods.•Selecting final preferable solution using DEA super efficiency of purchasing firms. Sustainable supplier selection is the process of identifying the appropriate supply partners of an organization with the most beneficial monetary value, while diminishing the various effects of its operations on society and environment. Therefore, it plays a significant role in moving an organization toward sustainable development. Alongside sustainable supplier selection, assigning proper quantity of orders to suppliers satisfying sustainability criteria is another activity that should be simultaneously carried out in order to develop a comprehensive tool in sustainable supplier management. Meanwhile, the issue of sustainable supplier selection and order allocation has attracted limited attention in the literature. The present paper aims at developing an inclusive multi-objective mixed integer linear programming model, which accounts for multiple periods, multiple products and multimodal transportation, to evaluate suppliers and allocate order quantities. Furthermore, the developed model that includes all sustainability aspects also takes both shortage and discount conditions into account. A hybrid three-step solution methodology is then presented, using which the original multi-objective problem is firstly converted to a single objective model by ε-constraint method. In the second step, the current single objective programming model is solved using the Benders decomposition algorithm that in turn is accelerated by a variety of algorithmic enhancements. Finally, among all the Pareto optimal solutions of the original multi-objective programming problem, the preferable solution is intelligently selected based on the DEA super efficiency score of all purchasing firms as a decision support tool. The applicability of the proposed approach is illustrated by a real-world case study in automotive industry.