Improved Variable Neighbourhood Search Algorithm for Robust Job Shop Scheduling Problems

Abstract

Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for solving combinatorial optimization problems. In this paper, an improved variable neighbourhood search (IVNS) algorithm is proposed to solve robust Job Shop Scheduling (JSS) problem with makespan as the performance criterion in which uncertain processing times are described by discrete scenarios. A new robust optimization model is established in single-stage production environments. The concept of robust optimization is proposed based on a set of bad scenarios, which is identified by a given threshold of performance for an associated schedule. The robust scheduling problem is formulated by minimizing an amount of penalty on the set of bad scenarios due to their poor performances.