• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.141-155
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• 2006

In this paper, we address an extended hub-and-spoke transportation network design problem (EHSNP). In the existing hub location problems, the location and number of spokes, and shipments on spokes are given as input data. These may, however, be viewed as the variables according to the areas which they cover. Also, the vehicle routing in each spoke needs to be considered to estimate the network cost more correctly. The EHSNP is a problem of finding the location of hubs and spokes, and pickup/delivery routes from each spoke, while minimizing the total related transportation cost in the network. The EHSNP is an integrated problem that consists of several interrelated sub-problems. To solve EHSNP, we present an approach based on a symbiotic evolutionary algorithm (symbiotic EA), which are known as an efficient tool to solve complex integrated optimization problems. First, we propose a framework of symbiotic EA for EHSNP and its genetic elements suitable for each sub-problem. To analyze the proposed algorithm, the extensive experiments are performed with various test-bed problems. The results show that the proposed algorithm is promising in solving the EHSNP.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.77-91
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• 2007

In this paper, we present a symbiotic evolutionary algorithm for multi-objective optimization. The goal in multi-objective evolutionary algorithms (MOEAs) is to find a set of well-distributed solutions close to the true Pareto optimal solutions. Most of the existing MOEAs operate one population that consists of individuals representing the entire solution to the problem. The proposed algorithm has a two-leveled structure. The structure is intended to improve the capability of searching diverse and food solutions. At the lower level there exist several populations, each of which represents a partial solution to the entire problem, and at the upper level there is one population whose individuals represent the entire solutions to the problem. The parallel search with partial solutions at the lower level and the Integrated search with entire solutions at the upper level are carried out simultaneously. The performance of the proposed algorithm is compared with those of the existing algorithms in terms of convergence and diversity. The optimization problems with continuous variables and discrete variables are used as test-bed problems. The experimental results confirm the effectiveness of the proposed algorithm.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.36 no.1
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• pp.71-77
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• 2010

The water fern Azolla belongs to the Azollaceae and forms a symbiotic association with a $N_2$-fixing cyanobacterium, referred to as Anabaena azollae, and this association has currently been demonstrated to have potential as a nitrogen source for rice production. Because of that, Azolla fern has been used not only as organic manure in southern China and northern Vietnam for a long time but also as food for animate creatures in the underwater and decontaminant in the water. However, the phenolic compounds and active materials of Azolla have not been examined in detail in the past studies. In the present study, anti-oxidant ability test and experiment to find a particular active material of Azolla imbricata and Azolla imbricata fraction (AIF) were performed. In anti-oxidant test such as DPPH test and lipoxygenase inhibition test, the value of test represented high activities compared with authentic sample - green tea and NDGA (nordihydroguaiaretic acid). In MMP-1 test, related to collagen protection and elasticity of skin, its inhibitory effect was measured over 75 %, and the phenolic compounds of AIF related with this activity were confirmed luteolin derivatives by using FT-IR spectroscopy, element analyzer (EA) and Liquid chromatography-MASS spectroscopy.