Simultaneous scheduling of jobs and transporters in a hybrid flow shop with collision-free transporter routing: A novel parallel heuristic

Abstract

A computationally potent two-stage parallel heuristic (TSPH) and a mixed integer linear programming (MILP) are suggested to address the simultaneous scheduling of jobs and transporters in a hybrid flow shop system, wherein multiple transporters, stage omission, transporter eligibility, machine eligibility, and collision-free transporter routing are assumed. To the best of our knowledge, the significance of transporter collision-free routing has not been spotlighted in the literature on flow shop systems. Collision-free routing of transporters is a requisite technical attribute as transport means may collide on routes and break down the whole system. Our MILP and TSPH assume collision-free routing to impede the issue. Being equipped with parallel computing, TSPH can deal with large problems in a considerably short time. To support, TSPH is analogized against the suggested MILP, two-step MILP (TSMILP), and an efficient parallel meta-heuristic (i.e., parallel particle swarm optimization and genetic algorithm (PPSOGA)) that outperformed many literarily prominent meta-heuristics in the literature. The benchmark results uncover that TSPH outclasses both TSMILP and PPSOGA in the quality of solutions. Eventually, utilizing the convergence plot and Nemenyi’s post-hoc procedure for Friedman’s test, it is revealed that the outcomes of TSPH are remarkably more desirable than those of TSMILP and PPSOGA.