MOEA/D : A multiobjective evolutionary algorithm based on decomposition
|Journal / Publication||IEEE Transactions on Evolutionary Computation|
|Publication status||Published - Dec 2007|
|Link to Scopus||https://www.scopus.com/record/display.uri?eid=2-s2.0-34548108555&origin=recordpage|
Decomposition is a basic strategy in traditional multiobjective optimization. However, it has not yet been widely used in multiobjective evolutionary optimization. This paper proposes a multiobjective evolutionary algorithm based on decomposition (MOEA/D). It decomposes a multiobjective optimization problem into a number of scalar optimization subproblems and optimizes them simultaneously. Each subproblem is optimized by only using information from its several neighboring subproblems, which makes MOEA/D have lower computational complexity at each generation than MOGLS and nondominated sorting genetic algorithm II (NSGA-II). Experimental results have demonstrated that MOEA/D with simple decomposition methods outperforms or performs similarly to MOGLS and NSGA-II on multiobjective 0-1 knapsack problems and continuous multiobjective optimization problems. It has been shown that MOEA/D using objective normalization can deal with disparately-scaled objectives, and MOEA/D with an advanced decomposition method can generate a set of very evenly distributed solutions for 3-objective test instances. The ability of MOEA/D with small population, the scalability and sensitivity of MOEA/D have also been experimentally investigated in this paper. © 2007 IEEE.
- Computational complexity, Decomposition, Evolutionary algorithm, Multiobjective optimization, Pareto optimality
IEEE Transactions on Evolutionary Computation, Vol. 11, No. 6, 12.2007, p. 712-731.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal
Zhang, Q & Li, H 2007, 'MOEA/D: A multiobjective evolutionary algorithm based on decomposition', IEEE Transactions on Evolutionary Computation, vol. 11, no. 6, pp. 712-731. https://doi.org/10.1109/TEVC.2007.892759