Iterative-Sampling Search for Job Shop Scheduling with Setup Times

Abstract

This paper presents a heuristic algorithm for solving the job-shop scheduling problem with sequence dependent setup times (SDST-JSSP). The algorithm relies on a core constraint-based search procedure, which generates consis-tent ordering of activities requiring the same resource by in-crementally imposing precedence constraints on a temporal feasible solution. Key to the effectiveness of the search pro-cedure is a conflict sampling method biased toward selection of most critical conflict and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This constraint-based search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically on a set of previously studied job-shop scheduling benchmark problems with sequence dependent setup times.