Fuzzy TOPSIS based selection index in the planning of emergency service facilities locations and goods transportation
| Autor: | Bidzina Matsaberidze, David Mikadze, Bidzina Midodashvili, Bezhan Ghvaberidze, Gia Sirbiladze |
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| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Service (business) 0209 industrial biotechnology Index (economics) Operations research Computer science Fuzzy topsis General Engineering 02 engineering and technology 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Selection (genetic algorithm) |
| Zdroj: | Journal of Intelligent & Fuzzy Systems. 41:1949-1962 |
| ISSN: | 1875-8967 1064-1246 |
| Popis: | The attributes influencing the decision-making process in planning transportation of goods from selected facilities locations in disaster zones are considered. Experts evaluate each candidate for humanitarian aid distribution centers (HADCs) (service centers) against each uncertainty factor in q-rung orthopair fuzzy sets (q-ROFS). For representation of experts’ knowledge in the input data for planning emergency service facilities locations a q-rung orthopair fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach is developed. Based on the offered fuzzy TOPSIS aggregation a new innovative objective function is introduced which maximizes a candidate HADC’s selection index and reduces HADCs opening risks in disaster zones. The HADCs location and goods transportation problem is reduced to the bi-criteria problem of partitioning the set of customers by the set of service centers: 1) Minimization of opened HADCs and goods transportation total costs; 2) Maximization of HADCs selection index. Partitioning type transportation constraints are also constructed. Our approach for solving the constructed bi-criteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a new matrix with columns allowing to find all possible partitioning of the demand points with the opened HADCs. In the second phase, using the generated matrix and our exact algorithm we find the partitioning –allocations of the HADCs to the centers corresponded to the Pareto-optimal solutions. The constructed model is illustrated with a numerical example. |
| Databáze: | OpenAIRE |
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