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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Takahashi, R. |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Syst. & Inf. Eng., Hachinohe Inst. of Technol., Hachinohe, Japan (Takahashi, R.) |
| Abstract | Efficiency to search for the optimum solutions of the traveling salesman problem (TSP) and controlling the diversity of the population are quantitatively evaluated for iterative Extended Changing Crossover Operators (i-ECXO), immune Genetic Algorithm (immune-GA) and Thermo Dynamical Genetic Algorithm (TDGA). i-ECXO is a hybrid method to unite Edge Assembly Crossover (EAX) to Ant Colony Optimization (ACO). It mixes chromosomes generated by ACO which has capability to create closed tours with different sequences of visiting cities with those generated by EAX which has capacity to search for the best local solutions efficiently. It makes EAX reproduce better individuals by reusing the mixed chromosomes as initial tours. In TDGA the diversity of the population is accurately calculated as entropy H and selects out individuals so that free energy F can be minimized. Immune-GA realizes Jerne's network which harmonizes the immune system by making another antibodies work antigens for each antibody. Regards as capability of controlling the diversity of the population, above three methods are evaluated by using the edges' entropy H in TDGA. C and Java experimental results using medium-sized TSPLIB data such as fl417 are reported in this paper. |
| Starting Page | 235 |
| Ending Page | 244 |
| File Size | 621860 |
| Page Count | 10 |
| File Format | |
| ISSN | 21579563 |
| e-ISBN | 9781479951512 |
| DOI | 10.1109/ICNC.2014.6975841 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hybrid method Entropy Statistics TDGA ACO Biological cells Genetic algorithms Convergence TSP Sociology Cities and towns immune-GA iterative ECXO EAX |
| Content Type | Text |
| Resource Type | Article |
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