An integrated decision support system for berth and ship unloader allocation in bulk material handling port

Pratap, Saurabh (Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Hong Kong, China) ; Nayak, Ashutosh (Department of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India) ; Kumar, Akhilesh (Department of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India) ; Cheikhrouhou, Naoufel (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Kumar Tiwari, Manoj (Department of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India)

Berth 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.


Mots-clés:
Type d'article:
scientifique
Ecole:
HEG-GE
Institut:
Centre de Recherche Appliquée en Gestion
Classification:
Économie/gestion
Date:
2017
Pagination:
14 p.
Titre du document hôte:
Computers & industrial engineering
Numérotation (vol. no.):
2017, vol. 106, pp. 386–399
DOI:
ISSN:
0360-8352
Le document apparaît dans:



 Notice créée le 2017-04-10, modifiée le 2017-04-10

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