Heuristic and exact algorithms for single-machine scheduling problems with general truncated learning effects

被引：0
|
作者：
Ji-Bo Wang
Li-Han Zhang
Zheng-Guo Lv
Dan-Yang Lv
Xin-Na Geng
Xinyu Sun
机构：
[1] Shenyang Aerospace University,School of Computer Science
[2] Xi’an Jiaotong University,School of Management
来源：
Computational and Applied Mathematics | 2022年 / 41卷
关键词：
Scheduling; Branch-and-bound; Learning effect; Tabu search; Simulated annealing; 90B35; 90C26;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper addresses single-machine scheduling problems with truncated learning effects. The objective is to determine the optimal job schedule such that the makespan, the total weighted completion time and the maximum lateness are to be minimized. All the considered problems are NP-hard; hence, for each problem, we propose the heuristic and branch-and-bound algorithms. Extensive numerical experiments validate the efficiency of the proposed solution algorithms on a set of randomly generated instances.
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