In the last years, a set of bio-inspired metaheuristics has proved their efficiencies in combinational and continues optimization areas. This paper intends to hybrid a discrete version of Bat algorithm (BA) with Gener...
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In the last years, a set of bio-inspired metaheuristics has proved their efficiencies in combinational and continues optimization areas. This paper intends to hybrid a discrete version of Bat algorithm (BA) with generalized evolutionary walk algorithm (GEWA) to solve the mono-processors two stages Hybrid Flow Shop scheduling. The authors compare the modified bat algorithm with the original one, with Particle Swarm Optimization (PSO) and with others results taken from literature. Computational results on a standard two-stage hybrid flow shop benchmark of 70 cases, and about 1700 instances, indicate that the proposed algorithm finds the best makespan (Cmax) in a good processing time comparing to the original bat algorithm and other algorithms.
In this paper, two metaheuristics, namely the Bat algorithm (BAT) and a recent hybridization of bat algorithm with generalizedwalkevolutionaryalgorithm are presented. The bat algorithm and the Bat algorithm with ge...
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In this paper, two metaheuristics, namely the Bat algorithm (BAT) and a recent hybridization of bat algorithm with generalizedwalkevolutionaryalgorithm are presented. The bat algorithm and the Bat algorithm with generalized flight (BAG) are used to solve the problem of optimal redundancy design of series-parallel electrical systems. In order to assess the reliability of the heterogeneous system of multi-state series-parallel, the Ushakov method a universal moment generating function (UMGF) is used to allow fast estimation. The design objective is to maximize the reliability of the bulk power generation system from wind farm. The components of each electrical subsystem are characterized by their performance (capacity), cost and reliability. Reliability is defined as the ability to satisfy consumer demand that is given by a cumulative load curve. By comparing three algorithms cited in this study, the results show that the hybridization of Bat and generalized evolutionary walk algorithm (BAG) are effective in solving the reliability redundancy optimization problem (RROP). Two illustrative examples are presented.
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