Finding Acceptable Solutions in the Pareto-Optimal Range using Multiobjective Genetic Algorithms

Author:

Bentley P. J.,Wakefield J. P.

Publisher

Springer London

Reference15 articles.

1. Bentley, P. J., 1996, Generic Evolutionary Design of Solid Objects using a Genetic Algorithm. Ph.D. Thesis, University of Huddersfield, Huddersfield, UK.

2. Dowsland, K. A., 1995, Simulated Annealing Solutions for Multi-Objective Scheduling and Timetabling. Applied Decision Technologies (ADT 95), London, 205-219.

3. Fonseca, C. M, & Fleming, P. J., 1995a,. An Overview of Evolutionary Algorithms in Multiobjective Optimization. Evolutionary Computation, 3:1, 1-16.

4. Fonseca, C. M., & Fleming, P. J., 1995b, Multiobjective Genetic Algorithms Made Easy: Selection, Sharing and Mating Restriction. Genetic Algorithms in Engineering Systems: Innovations and Applications, Sheffield, 45-52.

5. Linkens, D. A. & Nyongesa, H. O., 1993, A Distributed Genetic Algorithm for Multivariable Fuzzy Control. IEE Colloquium on Genetic Algorithms for Control Systems Engineering, Digest No. 199/130, 9/1-9/3.

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