Advanced Algorithms for the Reclaimer Scheduling Problem with Sequence-Dependent Setup Times and Availability Constraints

被引:0
作者
Benbrik, Oualid [1 ]
Benmansour, Rachid [1 ,2 ]
Elidrissi, Abdelhak [3 ]
Sifaleras, Angelo [4 ]
机构
[1] SI2M Lab INSEA, Rabat, Morocco
[2] Polytech Univ Hauts De France UVHC, INSA Hauts De France, LAMIH CNRS UMR 8201, Campus Mt Houy, F-59313 Valenciennes 9, France
[3] Int Univ Rabat, Rabat Business Sch, Parc Technopolis, Rabat, Morocco
[4] Univ Macedonia, Sch Informat Sci, Dept Appl Informat, 156 Egnatias Str, Thessaloniki 54636, Greece
来源
METAHEURISTICS, MIC 2024, PT I | 2024年 / 14753卷
关键词
Reclaimer Scheduling; Bulk Ports; Sequence-Dependent Setup Times; Availability Constraints; Machine Eligibility Restrictions; Variable Neighborhood Search; Heuristic;
D O I
10.1007/978-3-031-62912-9_28
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Scheduling of reclaimers activities in dry bulk terminals significantly impact terminal throughput, a crucial performance indicator for such facilities. This study addresses the Reclaimer Scheduling Problem (RSP) while considering periodic preventive maintenance activities for reclaimers. These machines are integral for reclaiming dry bulk materials stored in stockyards, facilitating their loading onto vessels via shiploaders. The primary aim of the objective function entails the minimization of the overall completion time, commonly referred to as the makespan. Since this problem is NP-hard, we propose a novel greedy constructive heuristic. The solutions obtained from this heuristic serve as the starting point for an efficient General Variable Neighborhood Search (GVNS) algorithm to handle medium-scale instances resembling real stockyard configurations. Computational experiments are conducted by comparing the proposed methods across various problem instances. The results demonstrate that the developed GVNS, coupled with the constructive heuristic for initial solution finding, efficiently improves scheduling efficacy. Thus, it emerges as a new state-of-the-art algorithm for this problem.
引用
收藏
页码:291 / 308
页数:18
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