Integrated scheduling problems of open shop and vehicle routing using an ensemble of group teaching optimization and simulated annealing

Abstract

Production and distribution are two parts of importance in supply chains. Yet, seldom attention is given to an integrated production and distribution in the case of open shop scheduling and vehicle routing problems. This article addresses an integrated scheduling problem of open shop and vehicle routing optimization, in which the jobs are processed in an open shop, and subsequently are delivered to customers at diverse places. First, a mixed integer programming model is developed to define the problem with minimizing maximum completion time. Second, an ensemble of group teaching optimization and simulated annealing methods is devised to optimally handle the considered problem. A heuristic rule is designed to generate a high-quality initial solution, while a simulated annealing method considering key machines is proposed to reinforce exploitation abilities. A nearest insertion method is used to make delivery decisions of vehicles. At last, the sensitivity analysis of user parameters in the developed approach is executed. Via solving a set of benchmark instances, we carry out extensive comparison experiments. The formulated model is verified by a mathematical programming optimizer CPLEX and the devised approach is compared with four meta-heuristics. The results and discussions confirm the strong competitiveness of the developed model and method for solving the concerned problems.