جلد 28، شماره 4 - ( Ijiepm 1396 )                   جلد 28 شماره 4 صفحات 403-427 | برگشت به فهرست نسخه ها

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Roshan K, Seifbarghy M, Pishva D. Multi-objective evolutionary algorithms for a preventive healthcare facility network design. IJIEPR. 2017; 28 (4) :403-427
URL: http://ijiepr.iust.ac.ir/article-1-754-fa.html
Multi-objective evolutionary algorithms for a preventive healthcare facility network design. نشریه بین المللی مهندسی صنایع و تحقیقات تولید. 1396; 28 (4) :403-427

URL: http://ijiepr.iust.ac.ir/article-1-754-fa.html


چکیده:   (439 مشاهده)

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. In this paper, a bi-objective mathematical model is proposed to design a network of preventive healthcare facilities so as to minimize total travel and waiting time as well as establishment and staffing cost. Moreover, each facility acts as M/M/1 queuing system. The number of facilities to be established, the location of each facility, and the level of technology for each facility to be chosen are provided as the main determinants of a healthcare facility network. Since the developed model of the problem is of an NP-hard type, tri-meta-heuristic algorithms are proposed to solve the problem. Initially, Pareto-based meta-heuristic algorithm called multi-objective simulated annealing (MOSA) is proposed in order to solve the problem. To validate the results obtained, two popular algorithms namely, non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are utilized. Since the solution-quality of all meta-heuristic algorithms severely depends on their parameters, Taguchi method has been utilized to fine tune the parameters of all algorithms. The computational results, obtained by implementing the algorithms on several problems of different sizes, demonstrate the reliable performances of the proposed methodology.

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نوع مطالعه: پژوهشي | موضوع مقاله: مدل های شبیه سازی و احتمالی
دریافت: ۱۳۹۶/۲/۲۷ | پذیرش: ۱۳۹۶/۷/۲۳ | انتشار: ۱۳۹۶/۷/۲۳

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