Variable neighborhood search-based subproblem solution procedures for a parallel shifting bottleneck heuristic for complex job shops

Abstract

The shifting bottleneck heuristic (SBH) for complex job shops decomposes the overall scheduling problem into a series of scheduling problems related to machine groups. These smaller, more tractable, scheduling problems are called subproblems. The heuristic is based on a disjunctive graph that is used to model the relationship between the sub-problems. In this paper, we use a parallel implementation of the SBH to assess the impact of a variable neighborhood search-based subproblem solution procedure (SSP) on global performance measures like the total weighted tardiness. Based on designed simulation experiments, we demonstrate the advantage of using high-quality SSPs.