سامانه مدیریت نشریات علمی دانشگاه شهید بهشتی

قیاسی, مریم سادات, وحدانی, بهنام. (1400). یک روش فراابتکاری برای مسئله مکان‌یابی مسیریابی هاب با تصمیمات ظرفیت و بالانس. , 11(3), 69-106. doi: 10.52547/jimp.11.3.69
مریم سادات قیاسی; بهنام وحدانی. "یک روش فراابتکاری برای مسئله مکان‌یابی مسیریابی هاب با تصمیمات ظرفیت و بالانس". , 11, 3, 1400, 69-106. doi: 10.52547/jimp.11.3.69
قیاسی, مریم سادات, وحدانی, بهنام. (1400). 'یک روش فراابتکاری برای مسئله مکان‌یابی مسیریابی هاب با تصمیمات ظرفیت و بالانس', , 11(3), pp. 69-106. doi: 10.52547/jimp.11.3.69
قیاسی, مریم سادات, وحدانی, بهنام. یک روش فراابتکاری برای مسئله مکان‌یابی مسیریابی هاب با تصمیمات ظرفیت و بالانس. , 1400; 11(3): 69-106. doi: 10.52547/jimp.11.3.69

یک روش فراابتکاری برای مسئله مکان‌یابی مسیریابی هاب با تصمیمات ظرفیت و بالانس

چشم‌انداز مدیریت صنعتی
دوره 11، شماره 3 - شماره پیاپی 43، مهر 1400، صفحه 69-106    اصل مقاله (1.82 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.52547/jimp.11.3.69
نویسندگان
مریم سادات قیاسی1؛ بهنام وحدانی* 2
1دانش آموخته مقطع کارشناسی ارشد، دانشگاه آزاد اسلامی، واحد قزوین، دانشکده مهندسی صنایع و مکانیک، گروه مهندس صنایع، قزوین، ایران.
2دانشیار، دانشگاه آزاد اسلامی، واحد قزوین، دانشکده مهندسی صنایع و مکانیک، گروه مهندس صنایع، قزوین، ایران.
چکیده
مسئله مکان‌یابی مسیریابی هاب یکی از مسائل کاربردی در دهه‌های اخیر است. پژوهش حاضر به یک مسئله مکان‌یابی مسیریابی هاب چندگانه می‌پردازد که در آن بهترین مکان‌ها برای هاب­‌ها و تورها برای هر هاب با دریافت و تحویل هم‌زمان تعیین می‌شوند. ابتدا یک مدل بهینه‌سازی برای به­‌حداقل­‌رساندن مجموع هزینه‌های ثابت مکان‌یابی مراکز، هزینه‌های جابه‌­جایی، سفر، تخصیص و هزینه‌های حمل‌ونقل پیشنهاد شده ‌است. به‌منظور دست‌­یافتن به ‌حل‌های کاربردی و عملی، هاب­‌ها ظرفیت محدودی دارند و هر گره می‌تواند توسط تخصیص تکی به هاب­‌ها اتصال یابد؛ همچنین ملاحظات بالانس با تخصیص تعداد مناسب گره‌­های تقاضا به هاب­‌ها به شبکه تحمیل می­‌شود. سپس مسئله با استفاده از نرم‌افزار GAMS برای نمونه‌هایی با اندازه کوچک حل می‌شود. با توجه به ماهیت NP-Hard مسئله، مدل بهینه‌سازی پیشنهادی توسط الگوریتم ژنتیک و الگوریتم رقابت استعماری حل خواهد شد. نتایج مقایسه‌ای حاصل از نمونه‌های مسئله نشان می‌دهد که الگوریتم ژنتیک عملکرد بهتری در مقایسه با الگوریتم رقابت استعماری دارد و در­نظر­گرفتن ملاحظات ظرفیت و بالانس می‌تواند در کاهش هزینه‌های شبکه موردبررسی مؤثر باشد.
کلیدواژه‌ها
مکانیابی مسیریابی هاب؛ سطوح ظرفیت؛ نیازمندی‌های بالانس؛ فراابتکاری
عنوان مقاله [English]
A Meta-Heuristic Approach for Hub Location-Routing Problem with Capacity and Balancing Decisions
نویسندگان [English]
Maryam Sadat Ghiasi1؛ Behnam Vahdani2
1MSc, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
2Associate Professor, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
چکیده [English]
Hub location-routing problem is a practical subject in the last decades. This study considers a many-to-many hub location-routing problem where the best locations of hubs and tours for each hub are determined with simultaneous pickup and delivery. First, an optimization model is proposed to minimize the total sum of fixed costs of locating hubs, the costs of handling, traveling, assigning, and transportation costs. To find practical solutions, the hubs have constrained capacity, in which single allocations can service every node to the hubs. What is more, the balancing requisites are imposed on the network by allocating the appropriate number of demand nodes to the hubs. Then the problem is solved using GAMS software for small-size instances of the problem. Due to the NP-hard nature of the problem, the proposed optimization model is solved by the Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA). For the problem instances, the comparative results indicate that GA has a better performance compared to ICA, and incorporating capacity and balancing considerations can influence the reduction of costs of the investigated network.    
کلیدواژه‌ها [English]
Location-Routing, Hub, Capacity Levels, Balancing Requirements, Meta-Heuristic Algorithm
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