This study investigates an energy-aware flow shop scheduling problem with a time-dependent learning effect. The relationship between the traditional and the proposed scheduling problem is shown and objective is to det...This study investigates an energy-aware flow shop scheduling problem with a time-dependent learning effect. The relationship between the traditional and the proposed scheduling problem is shown and objective is to determine a job sequence in which the total energy consumption is minimized. To provide an efficient solution framework, composite lower bounds are proposed to be used in a solution approach with the name of Boundsbased Nested Partition(BBNP). A worst-case analysis on shortest process time heuristic is conducted for theoretical measurement. Computational experiments are performed on randomly generated test instances to evaluate the proposed algorithms. Results show that BBNP has better performance than conventional heuristics and provides considerable computational advantage.展开更多
This study addresses the problem of two-stage scheduling on batch and single machines with limited waiting time constraint; thus, the makespan is minimized.A mixed-integer linear programming model is proposed for this...This study addresses the problem of two-stage scheduling on batch and single machines with limited waiting time constraint; thus, the makespan is minimized.A mixed-integer linear programming model is proposed for this problem. Three tight lower bounds and a heuristic algorithm are developed. The worst-case performance of the proposed algorithm is discussed. A hybrid differential evolution algorithm is also developed to improve the solution quantity. Numerical results show that the hybrid algorithm is capable of obtaining high-quality solutions and exhibits a competitive展开更多
文摘This study investigates an energy-aware flow shop scheduling problem with a time-dependent learning effect. The relationship between the traditional and the proposed scheduling problem is shown and objective is to determine a job sequence in which the total energy consumption is minimized. To provide an efficient solution framework, composite lower bounds are proposed to be used in a solution approach with the name of Boundsbased Nested Partition(BBNP). A worst-case analysis on shortest process time heuristic is conducted for theoretical measurement. Computational experiments are performed on randomly generated test instances to evaluate the proposed algorithms. Results show that BBNP has better performance than conventional heuristics and provides considerable computational advantage.
基金supported in part by National Natural Science Foundation of China (Grant Nos. 71690232 and 71371015)by National Science Foundation (Grant Nos. CMMI-1435800 and CMMI-1536978)
文摘This study addresses the problem of two-stage scheduling on batch and single machines with limited waiting time constraint; thus, the makespan is minimized.A mixed-integer linear programming model is proposed for this problem. Three tight lower bounds and a heuristic algorithm are developed. The worst-case performance of the proposed algorithm is discussed. A hybrid differential evolution algorithm is also developed to improve the solution quantity. Numerical results show that the hybrid algorithm is capable of obtaining high-quality solutions and exhibits a competitive
