حل مسئله زمان‌بندی و مسیریابی سبز وسایل حمل‏ونقل با ناوگان ناهمگن شامل لجستیک معکوس به شکل جمع‌آوری کالاهای بازگشتی با الگوریتم ژنتیک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

2 استاد، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران

چکیده

مسئله مسیریابی وسایل نقلیه (VRP)، یافتن مسیرهای بهینه برای ناوگانی از وسایل است که با سفر در آن مسیرها، تقاضای مشتریان برآورده می‏گردد. این مسئله از پرکاربردترین مسائل در حوزه حمل‌ونقل و تدارکات است. در این مقاله، مسئله زمان‌بندی و مسیریابی سبز وسایل حمل‏ونقل با ناوگان ناهمگن شامل لجستیک معکوس به شکل جمع‏آوری کالاهای بازگشتی با پنجره‏های زمانی چندگانه، توسعه داده شده است. این مسئله همراه با هزینه‌های زودکرد و دیرکرد وزن‏دهی شده برای ایجاد تبادلی بین هزینه‌های عملیاتی و زیست‏محیطی و با هدف حداقل‏سازی هم‌زمان به‌صورت برنامه‏ریزی غیرخطی مختلط، مدل‏سازی شده است. تقاضای مشتریان به صورت تقریبی و مبتنی بر اعداد فازی، در نظر گرفته شده که با توجه به وجود عدم قطعیت در برخی دیگر از پارامترها، از رویکرد برنامه‏ریزی امکانی استوار جهت کنترل، استفاده شده است. به دلیل قرارگیری مسئله موردنظر در رده مسائل NP-hard، الگوریتم ژنتیک جهت حل نزدیک به بهینه برای نمونه‌های ابعاد بزرگ، توسعه داده شده است. در نهایت، عملکرد الگوریتم پیشنهادی در مقایسه با حل معمولی در ابعاد کوچک با مثال‌هایی، ارزیابی شده است. تحلیل حساسیت و  آنالیز نتایج با تعریف دو معیار کیفیت راه‌حل و زمان محاسبات، عملکرد رضایت‌بخش الگوریتم پیشنهادی را در زمان محاسباتی مناسب نشان می‌دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Solving green vehicle routing and scheduling problem with heterogeneous fleet including reverse logistics in the form of collecting returned goods using genetic algorithm

نویسندگان [English]

  • Adel Aazami 1
  • Mohammad Saidi Mehrabad 2
1 Ph D. Candidate, Department of Industrial Engineering, Iran University of Science and Technology, Tehran
2 Professor, Department of Industrial Engineering, Iran University of Science and Technology, Tehran
چکیده [English]

Vehicle routing problem (VRP) is about finding optimal routes for a fleet of vehicles so that they can meet the demands for a set of given customers by traveling through those paths. This problem is one of the most important and most applicable problems of transportation and logistics scope. In this paper, green vehicle routing and scheduling problem with a heterogeneous fleet, including reverse logistics in the form of collecting returned goods along with weighted earliness and tardiness costs considering multiple time windows, is studied to establish a trade-off between operational and environmental costs. In this regard, a mixed-integer non-linear programming (MINLP) model is proposed at the first stage; then its accuracy and correct functioning are evaluated by solving some examples. Demand is considered uncertain based on fuzzy numbers that robust possibilistic programming is employed regarding the other parameters uncertainty. Since this problem is categorized as an NP-hard problem, a genetic algorithm (GA) is suggested to find near-optimal solutions for large instances in a rational computational time. Eventually, the GA’s performance is evaluated compared to solving the mathematical model for small-sized problems. Analysis of the results considering two criteria, solutions quality and computational times, indicates the satisfactory operation of the proposed algorithm in a proper computational time.  

کلیدواژه‌ها [English]

  • Genetic Algorithm
  • Green Vehicle Routing and Scheduling
  • reverse logistics
  • Heterogeneous Fleet
  • robust possibilistic programming
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