Honey Bee Colony Optimization for Multiresponse Mixed-Integer Problems
Goutam Barman
Goutam Barman, Assistant Professor, Department of Statistics, Krishnagar Government College, West Bengal, India.
Manuscript received on May 01, 2016. | Revised Manuscript received on May 02, 2016. | Manuscript published on May 05, 2016. | PP: 28-30 | Volume-6 Issue-2, May 2016. | Retrieval Number: B2835056216
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, honey bee optimization (HBO) is used to solve a multiple response optimization problem with mixed-integer (MI) search space. The work reported in this paper may be classified into six parts. The first part discusses on relevant literatures. In second and third part discusses about seemingly unrelated regression and desirability function. In fourth part discusses about two metaheuristics viz., ant colony optimization (ACO) and honey bee colony optimization. The fifth part provide the methodology of this study and in sixth part, the details of this research work illustrates. Standard single response test functions are selected to compare the performance of ACO and HBO. Statistical experimentation, seemingly unrelated regression (SUR), ‘maximin’ desirability function and HBO is used to solve the multiresponse optimization (MRO) problem. The results confirm the suitability of honey bee colony optimization for a typical multiresponse mixed integer problem.
Keywords: Ant Colony Optimization (ACO), Honey Bee Optimization (HBO), Seemingly Unrelated Regression (SUR), Desirability Function, Mixed-Integer (MI) Problem, Multiple Response Optimization (MRO