| In many practical applications, reasonable modeling and effective solution for optimization has become a very important research subject. With the expansion of the problem scale, the traditional optimization methods cannot effectively satisfy the desirableness; nowadays, using meta-heuristic method to solve the complicated combinatorial optimization problem has become a new hotspot. How to improve and design effective optimization method is the key to solving the problem.Bat Algorithm (BA) is a novel meta-heuristic optimization algorithm based on the echolocation behavior of micro-bats, which was proposed by Yang in2010. Not only it has the robustness and less parameter, but also it is easy to understand and program. So far, it has been applied in many engineering fields. However, the drawback of being trapped in local optimum and lower optimization accuracy has greatly limited the application range of BA.Aiming at some deficiencies existed in BA; this thesis will conduct deep research to the B A with the purpose of perfecting the basic B A and expanding the application domain of BA. In summary, the works in this thesis can be categorized into the following four aspects.1. Aiming at the phenomenon of slow convergence rate and low accuracy of BA, Levy flights trajectory is used to ensure the diversity of the population against premature convergence, Levy flights make the algorithm effectively jump out of local optimal. A differential operator is introduced to accelerate the convergence speed of the proposed algorithm, which makes the individual to communicate effectively among global optimal, individual history optimal and current individual. The differential operator effectively avoids premature and improves the performance of the bat algorithm.2. Based on the idea of BA and excellent characteristics of the cloud model on uncertainty knowledge representation. the conception of pulse emission rate and loudness is redefined. A new individual is generated by normal cloud generator transforming qualitative concepts to quantitative representation; Furthermore, Levy-flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. A bat algorithm based on cloud models is proposed, and the simulation results show that the novel bat algorithm based on cloud model has good performance on function optimization.3. The permutation flow shop problem (PFSP) is a discrete optimization problem. Firstly, this thesis adopted the continuous basic BA to solve PFSP. In order to make the bat algorithm is more suitable for discrete combination optimization problems, a discrete bat algorithm (DBA) based on the idea of continuous BA is proposed to solve PFSP. Experimental results and comparisons show the feasibility and effectiveness of the discrete bat algorithm for PFSP.4. The capacitated vehicle routing problem (CVRP) and aircraft landing problem (ALP) that not only are discrete combination optimization problems, but also are NP-hard problem with wide engineering and theoretical background. In this thesis, hybrid heuristic discrete bat algorithm is proposed to solve CVRP, and multiple runways case of the static ALP. In order to verify the validity of the method, many benchmarks are selected to test. Experimental results and comparisons show that the proposed algorithm is effective for CVRP and ALP, respectively. The proposed algorithm not only can obtain the high-quality and comparable solutions for instances up to500aircrafts, but also it is capable of finding optimal solutions for many instances in a short time. |
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