In this article, a continuous berth allocation problem is studied with stochastic ship arrival and handling times. The objective is to minimize a weighted sum of the expected waiting costs, berthing deviation costs and expected overtime costs. The sequence pair representation is utilized to project the solution space of the problem into two permutations. Then, a scenario-based method is used to capture the uncertainty. To effectively solve the problem over the sequence pair solution space, a simulated annealing is combined with two algorithms. One of the algorithms is used to determine the berthing positions and the other one is used to determine the berthing times. Computational experiments are conducted to evaluate the performance of the solution method and to verify the advantages of the proposed stochastic approach. The results indicate that the proposed methodology is both efficient and effective.
机构:
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Xiang Xi
;
Liu Changchun
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机构:
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Liu Changchun
;
Miao Lixin
论文数: 0引用数: 0
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机构:
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R China
Tsinghua Berkeley Shenzhen Inst, Intelligent Transportat & Logist Syst Lab, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
机构:
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Xiang Xi
;
Liu Changchun
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Liu Changchun
;
Miao Lixin
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R China
Tsinghua Berkeley Shenzhen Inst, Intelligent Transportat & Logist Syst Lab, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China