Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
Scheduling ocean transportation of crude oil
Management Science
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Fuzzy multiple attribute decision making: a review and new preference elicitation techniques
Fuzzy Sets and Systems - Special issue on fuzzy multiple criteria decision making
Container ship stowage problem: complexity and connection to the coloring of circle graphs
Discrete Applied Mathematics
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Principles of Combinatorial Optimization Applied to Container-Ship Stowage Planning
Journal of Heuristics
A parallel tabu search algorithm for solving the container loading problem
Parallel Computing - Special issue: Parallel computing in logistics
A computer-based decision support system for vessel fleet scheduling: experience and future research
Decision Support Systems
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary computing in manufacturing industry: an overview of recent applications
Applied Soft Computing
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Hydrodynamic Design of Control Surfaces for Ships Using a MOEA with Neuronal Correction
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
An OWA-TOPSIS method for multiple criteria decision analysis
Expert Systems with Applications: An International Journal
Simulated annealing for optimal ship routing
Computers and Operations Research
Learning-based ship design optimization approach
Computer-Aided Design
Review: A state-of the-art survey of TOPSIS applications
Expert Systems with Applications: An International Journal
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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.