Schaffer J D. Multi objective optimization with vector evaluated genetic algorithms[C]. Proc of the Int Conf on
[2]
Genetic Algorithms and Their Applications. Hillsdal: L Erlbaum Associates, Inc, 1985: 93-100.
[3]
Zitzler E, Thiele L, Lingle. Multi-objective
[4]
evolutionary algorithms: A comparative case study and the strength Pareto approach[J]. IEEE Trans on Evolutionary Computation, 1999: 3(4): 257-271.
[5]
Zitlzer E, Laumanns M, Thiele L. SPEA2: Improving the strength pareto evolutionary algorithm[C]. Proc of Int Conf on Evolutionary Method for Design, Optimization and Control with Applications to Industrial Problems. Berlin: Springer, 2002: 95-100.
[6]
Srinivas N, Deb K. Multiobjective optimization using non-dominated sorting in genetic algorithms[J]. Evolutionary Computation, 1994: 2(3): 221-248.
[7]
Deb K, Pratab A, Agarwal S, et al. A fast and elitist multi-objective genetic algorithm: NSGA-II[J]. IEEE Trans on Evolutionary Computation, 2002, 6(2): 182-197.
[8]
Knowles J D, Corne D W. Approximating the non-dominated front using the Pareto archived evolution strategy[J]. Evolutionary Computation, 2000, 8(2): 149-172.
[9]
Qingfu Zhang, Hui Li. MOEA/D: A multiobjective evolutionary algorithm based on decomposition[J]. IEEE Trans on Evolutionary Computation, 2007, 11(6): 712-731.
[10]
Goldberg, David E, Korb B, et al. Messy genetic algorithms: Motivation, analysis, and first results[J]. Complex Systems, 1989, 3(5): 493-530.
[11]
David A, Van Veldhuizen. Multiobjective optimization with messy genetic algorithms[C]. Proc of 2000 ACM Symposium On Applied Computing. Villa Olmo, 2000, 3: 470-476.
[12]
Jesse B, Zydallis, David A, et al. A statistical comparison of multiobjective evolutionary algorithms including the MOMOEA-II[C]. Proc of the 1st Int Conf on Evolutionary Multi-Criterion Optimization. 2001: 226-240.
[13]
Mitsukuni Matayoshi. Double chromosome GA with corner junction for solving the 2D strip packing problem[C]. IECON the 36th Annual Conf on IEEE Industrial Electronics Society. Glendale, 2010: 1110-1116.
[14]
Chen Guo, Ming Huang, Xu Liang. An improvement diploid genetic algorithm for job-shop scheduling problem[C]. The 18th Int Conf on Industrial Engineering and Engineering Management. Singapore, 2011, 9: 36-38.
[15]
Schopf J W. The evolution of the earliest cells[M]. Berlin: Scientific American, 1978: 110-138.
[16]
Fischer M, Hock M, Paschke M. Low genetic variation reduces cross compatibility and offspring fitness in populations of a narrow endemic plant with a self-incompatibility system[C]. Conservation Genetics. Netherlands: Kluwer Academic, 2011: 325-336.
[17]
Eckart Zitzler, Marco Laumanns, Stefan Bleule. A tutorial on evolutionary multiobjective optimization[C]. Wrokshop on Multiple Objective Metaheuristics. Berlin: Springer, 2004: 1-32.
[18]
Deb K, Mohan M, Mishra S. Evaluating the?varepsilon domination based multi-objective evolutionary algorithm for a quick computation of Pareto optimal solutions[J]. Evolutionary Computation, 2005, 13(4): 501-525.
[19]
Deb Kalyanmoy. Multi-objective genetic algorithm: Problem difficulties and construction of test problems[J]. Evolutionary Computation, 1999, 7(3): 205-230.
[20]
Deb K, Lothar T, Morco L, et al. Scalable test problems for evolutionary multi-objective optimization[C]. Evolutionary Multi-objective Optimization. Berlin: Springer Verlag, 2005: 105-145.
[21]
van Veldhuizen D A, Lamont G B. On measuring multi-objective evolutionary algorithm performance[C]. Congress on Evolutionary Computation. Piscataway: IEEE Press, 2000: 204-211.
[22]
Schoot J R. Fault tolerant design using single and multicriteria genetic algorithm optimization[D]. Cambridge: Massachusetts Institute of Technology, 1995.
[23]
Zitler E, Deb K, Thiele L. Comparison of multiobjective evolutionary algorithms: Empirical results[J]. Evolutionary Computation, 2000, 8(2): 173-195.