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A hybrid approach for multi-objective combinatorial optimisation problems in ship design and shipping

Olcer, A.I. (2008) A hybrid approach for multi-objective combinatorial optimisation problems in ship design and shipping. Computers & Operations Research, 35 (9). pp. 2760-2775. ISSN 0305-0548

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Abstract

Numerous real-world problems relating to ship design and shipping are characterised by combinatorially explosive alternatives as well as multiple conflicting objectives and are denoted as multi-objective combinatorial optimisation (MOCO) problems. The main problem is that the solution space is very large and therefore the set of feasible solutions cannot be enumerated one by one. Current approaches to solve these problems are multi-objective metaheuristics techniques, which fall in two categories: population-based search and trajectory-based search. This paper gives an overall view for the MOCO problems in ship design and shipping where considerable emphasis is put on evolutionary computation and the evaluation of trade-off solutions. A two-stage hybrid approach is proposed for solving a particular MOCO problem in ship design, subdivision arrangement of a ROPAX vessel. In the first stage, a multi-objective genetic algorithm method is employed to approximate the set of pareto-optimal solutions through an evolutionary optimisation process. In the subsequent stage, a higher-level decision-making approach is adopted to rank these solutions from best to worst and to determine the best solution in a deterministic environment with a single decision maker.

Item type: Article
ID code: 19763
Keywords: multi-objective combinatorial optimisation, genetic algorithms, pareto-optimal concept, multiple attribute decision making, TOPSIS, Hydraulic engineering. Ocean engineering, Modelling and Simulation, Management Science and Operations Research, Computer Science(all)
Subjects: Technology > Hydraulic engineering. Ocean engineering
Department: Faculty of Engineering > Naval Architecture and Marine Engineering
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 02 Jun 2010 18:19
    Last modified: 05 Sep 2014 02:37
    URI: http://strathprints.strath.ac.uk/id/eprint/19763

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