• IE interfaces
• /
• v.17 no.spc
• /
• pp.20-27
• /
• 2004

A flexible assembly system (FAS) is a production system that assembles various parts with many constraints and manufacturing flexibilities. This paper presents a new method for efficiently solving the integrated process planning and scheduling in FAS. The two problems of FAS process planning and scheduling are tightly related with each other. However, in almost all the existing researches on FAS, the two problems have been considered separately. In this research, an endosymbiotic evolutionary algorithm is adopted as methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary algorithm to solving the integrated problem. Some evolutionary schemes are used in the algorithm to promote population diversity and search efficiency. The experimental results are reported.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.26 no.4
• /
• pp.109-124
• /
• 2001

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed model assembly lines (MMALs). Line balancing and model sequencing are important for an efficient use of MMALs. The two problems of balancing and sequencing MMALs are tightly related with each other. However, In almost all the existing researches on mixed-model production lines, the two problems have been considered separately. In this research, an endosymbiotic evolutionary a1gorithm, which is a kind of coevolutionary a1gorithm, is adopted as a methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary a1gorithm to solving the integrated problem. Some evolutionary schemes are used In the a1gorithm to promote population diversity and search efficiency. The proposed a1gorithm is compared with the existing evolutionary algorithms in terms of solution quality and convergence speed. The experimental results confirm the effectiveness of our approach.

• Journal of Korean Institute of Industrial Engineers
• /
• v.37 no.1
• /
• pp.1-9
• /
• 2011

This paper presents a new method that can solve the integrated problem of combined location routing and inventory problem (CLRIP) efficiently. The CLRIP is used to establish facilities from several candidate depots, to find the optimal set of vehicle routes, and to determine the inventory policy in order to minimize the total system cost. We propose a mathematical model for the CLRIP with budget constrained. Because this model is a nonpolynomial (NP) problem, we propose a endosymbiotic evolutionary algorithm (EEA) which is a kind of symbiotic evolutionary algorithm (SEA). The heuristic method is used to obtaining the initial solutions for the EEA. The experimental results show that EEA perform very well compared to the existing heuristic methods with considering inventory control decisions.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.37 no.3
• /
• pp.39-55
• /
• 2012

This paper presents an endosymbiotic evolutionary algorithm (EEA) to solve both problems of line balancing and model sequencing in a mixed-model two-sided assembly line (MMtAL) simultaneously. It is important to have a proper balancing and model sequencing for an efficient operation of MMtAL. EEA imitates the natural evolution process of endosymbionts, which is an extension of existing symbiotic evolutionary algorithms. It provides a proper balance between parallel search with the separated individuals representing partial solutions and integrated search with endosymbionts representing entire solutions. The strategy of localized coevolution and the concept of steady-state genetic algorithms are used to improve the search efficiency. The experimental results reveal that EEA is better than two compared symbiotic evolutionary algorithms as well as a traditional genetic algorithm in solution quality.

• Animal cells and systems
• /
• v.5 no.4
• /
• pp.291-297
• /
• 2001

Three species of endosymbiotic dinoflagellates, zooxanthellae, are investigated from six host species of anthozoans from Korea. Three unrecorded endosymbionts species are Symbiodinium kawagutii, Symbiodinium microadriaticum, and Symbiodinium sp. Symbiodinium kawagutii Is associated with Alveopora japonica, Anthopleura japonica and Parasicyonis actinostoloides. Symbiodinium microadiraticum is found in Anthopleura kurogane and Parasicyonis sp. Unlike the former two symbionts, Symbiodinium sp. is associated with Anthopleura midori.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.1048-1055
• /
• 2003

This paper proposes a new method of solving integrated problems that consist of several sub-problems in a symmetric multi-layered structure, and also demonstrate the applicability of the method. The proposed method is named Symmetric Multi-layered Coevolutionary Algorithm (SMCA). The SMCA imitates partly the natural process of endosymbiotic evolution, which is a special type of coevolution. The SMCA is applied to the process planning problem in flexible manufacturing system (FMS), taking account of the flexibility of machine, tool, process, and sequence. To do this, SMCA's components are studied and its strategies are developed to improve the performance. The proposed algorithm is compared with the existing ones in terms of solution quality. The experimental results confirm the effectiveness of our approach.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.930-935
• /
• 2002

This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problem are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed­model production lines, the two problems have been considered separately. In 1his research, an endosymbiotic evolutionary algorithm, which is a kind of evolutionary algorithm, is adopted as a methodology in order to solve the two problems simultaneously. Some evolutionary search capability, rapidity of convergence and population diversity. The proposed algorithm is compared with the existing evolutionary algorithm in terms of solution quality. The experimental results confirm the effectiveness of our approach.

• Current Research on Agriculture and Life Sciences
• /
• v.30 no.2
• /
• pp.115-123
• /
• 2012

Whiteflies harbor several secondary endosymbionts, which are maternally inherited from mother to offspring, that have major effects on host preferences, biology, and evolution. Here, we identified Wolbachia bacteria in sweetpotato whitefly (Bemisia tabaci) as well as whitefly popluations from other countries by comparison of 16S rDNA sequences. Wolbachia were detected in all tested indigenous B. tabaci populations (Bangladesh, Myanmar, Nepal, and the Philippines) as well as Q1 biotype of Korea, whereas they were absent from B biotype of Korea and Q biotype of China. Wolbachia were also detected in all five tested Aleurodicus dispersus populations as well as Tetraleurodes acaciae, whereas they were not detected in all seven Trialeurodes vaporariorum populatuions. In addiiton, Wolbachia were detected in parasitic wasp (Encarsia formosa) of B. tabaci as well as honeybee (Apis mellifera). Among the 19 whitefly populations from different countries, our analysis identified four phylogenetic groups of Wolbachia, thereby demonstrating the high diversity of this genus. Wolbachia phylogeny suggests a correlation of geographical range with ecological variation at the species level.

• Parasites, Hosts and Diseases
• /
• v.54 no.3
• /
• pp.265-272
• /
• 2016

Wolbachia is an obligatory intracellular endosymbiotic bacterium, present in over 20% of all insects altering insect reproductive capabilities and in a wide range of filarial worms which is essential for worm survival and reproduction. In Egypt, no available data were found about Wolbachia searching for it in either mosquitoes or filarial worms. Thus, we aimed to identify the possible concurrent presence of Wolbachia within different mosquitoes and filarial parasites, in Assiut Governorate, Egypt using multiplex PCR. Initially, 6 pools were detected positive for Wolbachia by single PCR. The simultaneous detection of Wolbachia and filarial parasites (Wuchereria bancrofti, Dirofilaria immitis, and Dirofilaria repens) by multiplex PCR was spotted in 5 out of 6 pools, with an overall estimated rate of infection (ERI) of 0.24%. Unexpectedly, the highest ERI (0.53%) was for Anopheles pharoensis with related Wolbachia and W. bancrofti, followed by Aedes (0.42%) and Culex (0.26%). We also observed that Wolbachia altered Culex spp. as a primary vector for W. bancrofti to be replaced by Anopheles sp. Wolbachia within filaria-infected mosquitoes in our locality gives a hope to use bacteria as a new control trend simultaneously targeting the vector and filarial parasites.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.35 no.3
• /
• pp.25-43
• /
• 2010

We consider a multi-objective balancing and sequencing problem in mixed model assembly lines, which is important for an efficient use of the assembly lines. In this paper, we present a neighborhood symbiotic evolutionary algorithm to simultaneously solve the two problems of balancing and model sequencing under multiple objectives. We aim to find a set of well-distributed solutions close to the true Pareto optimal solutions for decision makers. The proposed algorithm has a two-leveled structure. At Level 1, two populations are operated : One consists of individuals each of which represents a partial solution to the balancing problem and the other consists of individuals for the sequencing problem. Level 2, which is an upper level, works one population whose individuals represent the combined entire solutions to the two problems. The process of Level 1 imitates a neighborhood symbiotic evolution and that of Level 2 simulates an endosymbiotic evolution together with an elitist strategy to promote the capability of solution search. The performance of the proposed algorithm is compared with those of the existing algorithms in convergence, diversity and computation time of nondominated solutions. The experimental results show that the proposed algorithm is superior to the compared algorithms in all the three performance measures.