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Posts
Blog Post number 4
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Blog Post number 1
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publications
Investigation on Efficiency of Optimal Mixing on Various Linkage Sets
Published in CEC, 2014
The optimal mixing operator(OM) utilizes linkage sets (LSs) to exchange the information of variables between a pair of solutions, and the result of such exchange is adopted only if the exchange leads to improvement of the solution quality. The performance of OM highly depends on the LS it uses. This paper demonstrates that previously proposed LS, the linkage tree model (LT), does not yield the optimal performance. To measure the efficiency of OM on different LSs, the cost-performance (CP) index is defined. Both our CP index and experiments indicate (1) that for fully separable problems, the most suitable LS is the marginal product model (MP), and (2) that for separable problems with overlap, LT is more suitable than MP, and (3) that properly pruned LT leads to higher efficiency and yields a better performance, and (4) that the LS that properly reflects the problem structure yields the best performance on both fully separable problems and problems with overlap.
Recommended citation:
Y.-F. Tung and T.-L. Yu. Theoretical perspective of convergence complexity of evolutionary algorithms adopting optimal mixing. Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO-2015), pages 535-542. ACM, 2015.
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Theoretical perspective of convergence complexity of evolutionary algorithms adopting optimal mixing
Published in GECCO, 2015
The optimal mixing evolutionary algorithms (OMEAs) have recently drawn much attention for their robustness, small size of required population, and efficiency in terms of number of function evaluations (NFE). In this paper, the performances and behaviors of OMEAs are studied by investigating the mechanism of optimal mixing (OM), the variation operator in OMEAs, under two scenarios – one-layer and two-layer masks. For the case of one-layer masks, the required population size is derived from the viewpoint of initial supply, while the convergence time is derived by analyzing the progress of sub-solution growth. NFE is then asymptotically bounded with rational probability by estimating the probability of performing evaluations. For the case of two-layer masks, empirical results indicate that the required population size is proportional to both the degree of cross competition and the results from the one-layer-mask case. The derived models also indicate that population sizing is decided by initial supply when disjoint masks are adopted, that the high selection pressure imposed by OM makes the composition of sub-problems impact little on NFE, and that the population size requirement for two-layer masks increases with the reverse-growth probability.
Recommended citation:
Y.-F. Tung and T.-L. Yu. Theoretical perspective of convergence complexity of evolutionary algorithms adopting optimal mixing. Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO-2015), pages 535-542. ACM, 2015.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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