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Improving the bees algorithm for complex optimisation problems

Otri, Sameh 2011. Improving the bees algorithm for complex optimisation problems. PhD Thesis, Cardiff University.

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Abstract

An improved swarm-based optimisation algorithm from the Bees Algorithm family for solving complex optimisation problems is proposed. Like other Bees Algorithms, the algorithm performs a form of exploitative local search combined with random exploratory global search. This thesis details the development and optimisation of this algorithm and demonstrates its robustness. The development includes a new method of tuning the Bees Algorithm called Meta Bees Algorithm and the functionality of the proposed method is compared to the standard Bees Algorithm and to a range of state-of-the-art optimisation algorithms. A new fitness evaluation method has been developed to enable the Bees Algorithm to solve a stochastic optimisation problem. The new modified Bees Algorithm was tested on the optimisation of parameter values for the Ant Colony Optimisation algorithm when solving Travelling Salesman Problems. Finally, the Bees Algorithm has been adapted and employed to solve complex combinatorial problems. The algorithm has been combined with two neighbourhood operators to solve such problems. The performance of the proposed Bees Algorithm has been tested on a number of travelling salesman problems, including two problems on printed circuit board assembly machine sequencing.

Item Type: Thesis (PhD)
Status: Unpublished
Schools: Engineering
Uncontrolled Keywords: Bees algorithm ; Ant colony optimisation ; Swarm intelligence ; Optimisation technique ; Combinatorial optimisation ; Continuous optimisation ; Optimisation problem
Date of First Compliant Deposit: 30 March 2016
Last Modified: 15 Dec 2017 08:57
URI: http://orca.cf.ac.uk/id/eprint/11568

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