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Abstract:
Time-of-use (TOU) electricity pricing policy is widely encountered in the world, which provides new opportunities for power-intensive enterprises to save their energy cost. A good trade-off between the total electricity cost and production efficiency is desired by decision makers. Thiswork addresses an energy-conscious bi-objective single-machine batch scheduling problem under TOU electricity tariffs, in which electricity price varies with time. The objective of the problem is to simultaneously minimize total electricity cost and makespan. Due to its strong NP-hard nature, two fast new epsilon-constraint-based constructive heuristic algorithms are developed to solve it. The core idea is to transform the bi-objective problem into a series of single-objective problems that are fast and heuristically solved to obtain an approximate Pareto front. Especially, for each transformed single-objective problem, two novel constructive heuristic algorithms are proposed by solving a series of multiple knapsack problems and 0-1 knapsack problems, respectively. Computational results on 145 benchmark and 80 newly generated larger-scale instances show that the proposed algorithms are quite efficient and are able to find high-quality Pareto solutions for large-scale problems with up to 200 batches.
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ANNALS OF OPERATIONS RESEARCH
ISSN: 0254-5330
Year: 2019
2 . 5 8 3
JCR@2019
4 . 4 0 0
JCR@2023
ESI Discipline: ENGINEERING;
ESI HC Threshold:150
CAS Journal Grade:3
Cited Count:
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 1
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