A disjunctive graph and shifting bottleneck heuristics for multi hoists scheduling problem

Abstract In this paper, we studied a multi hoists scheduling problem with transportation constraints. For each job, there are several operations which can be operated on a set of machines (tanks), and their operation times are bounded. The transportation tasks are performed by several available transport resources. The objective is to determine an assignment of processing and transport resources and valid schedules on them without storage for both processing and transport operations while minimizing makespan. The assignments and schedules can be efficiently modeled by a disjunctive graph: negative arcs present the maximum processing and transportation times, and the length of the longest path without positive cycle represents the makespan of a feasible solution without storage. A modified genetic algorithm is used to do the assignment of tasks on resources. A modified Shifting Bottleneck procedure is applied to find a schedule for both machines’ and transports’ operations for a specific individual. Computational results for benchmark instances with several transport resources are presented.