000001968 001__ 1968
000001968 005__ 20190411205441.0
000001968 022__ $$a0360-8352
000001968 0247_ $$a10.1016/j.cie.2016.12.009$$2DOI
000001968 037__ $$aARTICLE
000001968 041__ $$aeng
000001968 245__ $$aAn integrated decision support system for berth and ship unloader allocation in bulk material handling port
000001968 260__ $$c2017
000001968 269__ $$a2017-04
000001968 300__ $$a14 p.
000001968 506__ $$avisible
000001968 520__ $$aBerth allocation and material handling problems in ports are generally solved independently. This article provides a framework for aligning allocation decisions of berth and ship un-loader in an integrative manner. The ultimate goal of these decisions is to minimize the waiting time, operating time and ships priority deviation. As the sojourn time of a ship in port is costly, and given the scale and the complexity of the problem, a Decision Support System (DSS) is developed for the port authority. Two different approaches have been considered in this paper: (1) Solving the problem sequentially by decomposing the problem into two sub-problems- the berth allocation and the dynamic allocation of ship un-loaders in different berths (2) solving the problem by integrating berth allocation and dynamic allocation problem. Controlled Elitist Non-dominated Sorting Genetic Algorithm and Chemical Reaction Optimization are proposed in designing the DSS. Computational experiments are conducted on information provided from an Indian port. Results show that integrating berth and ship un-loader allocation achieves significant cost savings by considerably reducing the ship sojourn time in port.$$9eng
000001968 592__ $$aHEG - Genève
000001968 592__ $$bCRAG - Centre de Recherche Appliquée en Gestion
000001968 592__ $$cEconomie et Services
000001968 6531_ $$aship sequencing$$9eng
000001968 6531_ $$aberth allocation$$9eng
000001968 6531_ $$aship-unloader allocation$$9eng
000001968 6531_ $$abulk material handling terminal port$$9eng
000001968 6531_ $$ameta-heuristic$$9eng
000001968 655__ $$ascientifique
000001968 65017 $$aEconomie/gestion
000001968 700__ $$uDepartment of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong, China$$aPratap, Saurabh
000001968 700__ $$uDepartment of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India$$aNayak, Ashutosh
000001968 700__ $$uDepartment of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India$$aKumar, Akhilesh
000001968 700__ $$uHaute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale$$aCheikhrouhou, Naoufel
000001968 700__ $$aKumar Tiwari, Manoj$$uDepartment of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India
000001968 773__ $$g2017, vol. 106, pp. 386–399$$tComputers & industrial engineering
000001968 8564_ $$uhttps://hesso.tind.io/record/1968/files/Pr%C3%A9print.pdf$$s865759
000001968 8564_ $$xpdfa$$uhttps://hesso.tind.io/record/1968/files/Pr%C3%A9print.pdf?subformat=pdfa$$s23458993
000001968 906__ $$aGREEN
000001968 909CO $$pHEG_GE_ARTICLES_SCIENTIFIQUES_ECO$$pHEG_GE_ARTICLES_SCIENTIFIQUES$$pGLOBAL_SET$$ooai:hesso.tind.io:1968
000001968 950__ $$aI2
000001968 980__ $$ascientifique