Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm

• Published in: Journal of intelligent manufacturing Vol. 31; no. 4; pp. 1051 - 1078
• Main Authors: He, Lei, de Weerdt, Mathijs, Yorke-Smith, Neil
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2020; Springer Nature B.V
• Subjects: Adaptive algorithms; Advanced manufacturing technologies; Algorithms; Business and Management; Control; Domains; Earth observations (from space); Factor analysis; Heuristic methods; Hybridization; Integer programming; Intelligent manufacturing systems; Machines; Manufacturing; Mechatronics; Mixed integer; Neighborhoods; Orienteering; Processes; Production; Production capacity; Robotics; Satellite observation; Schedules; Scheduling; Search algorithms; Tabu search; Time dependence; Windows (intervals); Time windows; Hybrid algorithms; Adaptive large neighbourhood search; Time/sequence-dependent scheduling; Factor analysis; Tabu search
• ISSN: 0956-5515; 1572-8145; 1572-8145
• DOI: 10.1007/s10845-019-01518-4

In intelligent manufacturing, it is important to schedule orders from customers efficiently. Make-to-order companies may have to reject or postpone orders when the production capacity does not meet the demand. Many such real-world scheduling problems are characterised by processing times being dependent on the start time (time dependency) or on the preceding orders (sequence dependency), and typically have an earliest and latest possible start time. We introduce and analyze four algorithmic ideas for this class of time/sequence-dependent over-subscribed scheduling problems with time windows: a novel hybridization of adaptive large neighbourhood search (ALNS) and tabu search (TS), a new randomization strategy for neighbourhood operators, a partial sequence dominance heuristic, and a fast insertion strategy. Through factor analysis, we demonstrate the performance of these new algorithmic features on problem domains with varying properties. Evaluation of the resulting general purpose algorithm on three domains—an order acceptance and scheduling problem, a real-world multi-orbit agile Earth observation satellite scheduling problem, and a time-dependent orienteering problem with time windows—shows that our hybrid algorithm robustly outperforms general algorithms including a mixed integer programming method, a constraint programming method, recent state-of-the-art problem-dependent meta-heuristic methods, and a two-stage hybridization of ALNS and TS.