Kunihito Yamamori

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This correspondence describes a hybrid genetic algorithm (GA) to find high-quality solutions for the traveling salesman problem (TSP). The proposed method is based on a parallel implementation of a multipopulation steady-state GA involving local search heuristics. It uses a variant of the maximal preservative crossover and the double-bridge move mutation.(More)
This paper presents a parallel hybrid genetic algorithm (GA) for solving the sum-of-pairs multiple protein sequence alignment. A new chromosome representation and its corresponding genetic operators are proposed. A multi-population GENITOR-type GA is combined with local search heuristics. It is then extended to run in parallel on a multiprocessor system for(More)
This paper proposes a novel crossover operator for solving large-scale traveling salesman problems (TSPs) by using a Hybrid Genetic Algorithm (HGA) with Lin-Kernighan heuristic for local search and we tentatively name Zoning Crossover (Z-Cross). The outline of Z-Cross is firstly to set a zone in the travelling area according to some rules, secondly to cut(More)
Distortion of the waveform on Printed Circuit Board (PCBs) is a serious problem in higher-frequency signals transmission. To overcome this problem, we have already proposed segmental transmission line (STL). The STL divides transmission lines into multiple segments with different line widths, those are adjusted to reshape the signal waveform by(More)
This article proposes a novel crossover operator of hybrid genetic algorithms (HGAs) with a Lin-Kernighan (LK) heuristic for solving large-scale traveling salesman problems (TSPs). The proposed crossover, tentatively named sub-tour recombination crossover (SRX), collects many short sub-tours from both parents under some set of rules, and reconnects them to(More)
We investigated the relations between the physiological activities and protein expression levels of functional foods using a self-organizing map (SOM). The input vectors to the SOM were the protein expression levels and the physiological activity. A competitive node has two kinds of weights: one is for protein expression levels, and the other is for(More)
Experimental and analytical investigations are performed for OneMax problem using Wright–Fisher model. This study investigates the distribution of the first order schema frequency in the evolution process of Genetic Algorithm (GA). Effects of mutation in GA are analyzed for the standard mutation and asymmetric mutation models. If a population is in linkage(More)
Genetic algorithms (GAs) are stochastic optimization techniques, and the theoretical study of the process of GA evolution is very important in the application of GA. Mutation is one of most important operators in GA, and Markov chain theory has attracted researchers’ attention for the study of mutation. By applying Markov chain to study symmetric mutation(More)