New Lower Bound and Exact Method for the Continuous Berth Allocation Problem

上下界 数学优化 计算机科学 修剪 启发式 约束(计算机辅助设计) 周转时间 列生成 数学 几何学 农学 生物 操作系统 数学分析
作者
Zhou Xu,Chung‐Yee Lee
出处
期刊:Operations Research [Institute for Operations Research and the Management Sciences]
卷期号:66 (3): 778-798 被引量:27
标识
DOI:10.1287/opre.2017.1687
摘要

We study a continuous berth allocation problem, where incoming vessels need to be assigned a mooring time as well as a berth location on a quay. It is a crucial element in port planning to achieve quick turnaround time for vessels. To solve this problem, many solution methods have been developed in the literature. However, gaps between the best-known lower and upper bounds on its optimal solutions are far from close. In this paper, we propose new and more effective solution methods for this important problem. By introducing a novel relaxation of the problem, we have derived a new lower bound that can be computed efficiently in quadratic time. By incorporating this new lower bound with some new heuristic and pruning techniques, we have developed a new exact method, based on a branch-and-bound approach. To demonstrate general applicability of the proposed methods, we have extended them to a more complicated problem, where decisions on berth allocations are restricted by a quay crane constraint. Extensive computational results have shown that, compared with previous state-of-the-art methods, our new methods have significantly reduced gaps between the lower and upper bounds and have solved more and larger instances to optimality in significantly less time. We have also performed sensitivity tests to demonstrate how robust the new solutions are against uncertainties in particular input parameters. The online appendix is available at https://doi.org/10.1287/opre.2017.1687 .
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
ruochenzu发布了新的文献求助10
1秒前
1秒前
幸福无声发布了新的文献求助20
2秒前
奥福关注了科研通微信公众号
3秒前
3秒前
小井盖完成签到 ,获得积分10
4秒前
11111完成签到,获得积分10
4秒前
舒心妙旋完成签到,获得积分10
5秒前
xlx应助科研通管家采纳,获得10
6秒前
xlx应助科研通管家采纳,获得10
6秒前
情怀应助科研通管家采纳,获得10
6秒前
无花果应助科研通管家采纳,获得10
6秒前
科研通AI2S应助科研通管家采纳,获得10
6秒前
xlx应助科研通管家采纳,获得10
6秒前
小蘑菇应助科研通管家采纳,获得10
6秒前
BowieHuang应助科研通管家采纳,获得10
6秒前
Hello应助科研通管家采纳,获得10
6秒前
xlx应助科研通管家采纳,获得10
6秒前
Lny应助科研通管家采纳,获得10
6秒前
隐形曼青应助科研通管家采纳,获得10
6秒前
BowieHuang应助科研通管家采纳,获得10
6秒前
SciGPT应助科研通管家采纳,获得10
6秒前
xlx应助科研通管家采纳,获得10
6秒前
healthy应助科研通管家采纳,获得10
6秒前
6秒前
xlx应助科研通管家采纳,获得10
6秒前
7秒前
谢大喵发布了新的文献求助10
8秒前
12138发布了新的文献求助10
8秒前
an完成签到,获得积分10
9秒前
11秒前
升龙击完成签到,获得积分10
11秒前
12秒前
小马甲应助小马采纳,获得10
15秒前
12138完成签到,获得积分10
18秒前
周小熊完成签到 ,获得积分10
18秒前
大模型应助yushiolo采纳,获得10
18秒前
明天见完成签到,获得积分10
19秒前
19秒前
tian发布了新的文献求助10
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
人脑智能与人工智能 1000
King Tyrant 720
Silicon in Organic, Organometallic, and Polymer Chemistry 500
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 400
El poder y la palabra: prensa y poder político en las dictaduras : el régimen de Franco ante la prensa y el periodismo 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5604106
求助须知:如何正确求助?哪些是违规求助? 4688956
关于积分的说明 14857141
捐赠科研通 4696700
什么是DOI,文献DOI怎么找? 2541175
邀请新用户注册赠送积分活动 1507328
关于科研通互助平台的介绍 1471851