| 引用本文: | 黄涵,季彬.多目标约束处理方法求解泊位岸桥联合分配问题[J].控制理论与应用,2023,40(4):761~771.[点击复制] |
| HUANG Han,JI Bin.Multi-objective constraint handling method for solving berth allocation and quay crane assignment problem[J].Control Theory and Technology,2023,40(4):761~771.[点击复制] |
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| 多目标约束处理方法求解泊位岸桥联合分配问题 |
| Multi-objective constraint handling method for solving berth allocation and quay crane assignment problem |
| 摘要点击 1055 全文点击 356 投稿时间：2021-09-22 修订日期：2022-04-13 |
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| DOI编号 10.7641/CTA.2022.10891 |
| 2023,40(4):761-771 |
| 中文关键词 泊位岸桥联合分配 多目标优化 约束处理 遗传算法 |
| 英文关键词 berth allocation and quay crane assignment multi-objective optimization constraint handling genetic algorithms |
| 基金项目 国家自然科学基金项目(72001216, 71672193), 湖南省自然科学基金项目(2020JJ5780) |
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| 中文摘要 |
| 为了制定合理高效的泊位岸桥联合分配方案, 加快船舶周转, 本文针对船舶动态到港的连续泊位建立了以船舶总在港时间最短为目标的泊位岸桥联合分配混合整数非线性模型. 通过多目标约束处理策略将复杂约束的违反程度转化为另一个目标, 从而将原单目标优化模型转化为双目标优化模型, 并用基于快速非支配排序的多目标遗传算法(NSGA-II)对其进行求解. 同时, 针对问题特点, 分别设计了基于调整、惩罚函数、可行解优先和综合约束处 理策略的单目标遗传算法对原模型进行求解. 通过多组不同规模的标准算例对本文的方法进行测试, 验证了基于多目标约束处理策略的方法求解效果相较于单目标约束处理策略的方法更加高效和稳定. |
| 英文摘要 |
| A reasonable and efficient integrated berth allocation and quay crane assignment scheme can improve the efficiency of port operation and speed up vessels turnover. To achieve this, a mixed integer nonlinear model is established for continuous berth with dynamic vessel arrival, aiming at minimizing the total stay time of vessels in port. In this study, a multi-objective constraint handling strategy is presented to convert the complex constraints into an objective, so as to transform the original single-objective optimization model into a dual-objective optimization model, which is further solved by the non-dominated sorting based genetic algorithm (NSGA-II). In addition, other constraint handling strategies, such as the repair method, penalty function strategy, superiority of feasible solutions strategy and comprehensive strategy, are developed according to the characteristics of the problem, and incorporate with genetic algorithm to solve the original model. The test results on numerous instances show that the multi-objective constraint handling-based method is more efficient and stable than the single-objective constraint handling-based methods. |
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