نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری گروه مهندسی صنایع دانشکده مهندسی، دانشگاه بوعلی سینا، همدان

2 دانشیار گروه مهندسی صنایع دانشکده مهندسی، دانشگاه بوعلی سینا، همدان

چکیده

مساله مسیریابی تولید به تلفیق دو مساله مسیریابی خودرو و برنامه ریزی تولید می‌پردازد. عموما در مسئله فوق فرض بر این است که نوعی انحصار در محیط وجود دارد و توجهی به تاثیر رقبا در این مسائل در نظر گرفته نشده است. پر واضح است که در دنیای واقعی دیگر نمی‌توان به داشتن بازار انحصاری امید بست. در فضای رقابتی مشتریان متناسب با قیمت و کیفیت تامین‌کننده را انتخاب می‌کنند. بنابراین در این مقاله به عنوان تعریفی از کیفیت، تامین سریع نیاز مشتری و در دستری بودن الزام فضای رقابتی تبیین شده است و به همین جهت، مساله مسیریابی تولید رقابتی با فرض دانستن زودترین و دیرترین زمان تامین تقاضا توسط رقیب مدل‌بندی شده است. به این ترتیب در صورت تاخیر در تامین تقاضای مشتری به نسبت میزان تاخیر سهمی از بازار از دست می‌رود. همچنین مدل‌سازی انجام شده به وسیله نرم افزار گمز حل شده است. علاوه بر این به دلیل استفاده موفق الگوریتم بهینه‌سازی گروه ذرات در حل مسائل بهینه‌سازی، در اینجا نیز الگوریتم بهینه‌سازی گروه ذرات برای حل مساله مسیریابی تولید در ابعاد بزرگ توسعه داده می‌شود. برای بررسی عملکرد الگوریتم ارائه شده جواب‌های حاصل در ابعاد کوچک با جواب‌های حاصل از حل با نرم افزار گمز مقایسه شده است.
 

کلیدواژه‌ها

عنوان مقاله [English]

Particle Swarm Optimization to Solve Competitive Production Routing Problem

نویسندگان [English]

  • Farzaneh Adabi 1
  • Javad Behnamian 2

چکیده [English]

The production routing problem (PRP) integrates vehicle routing and production planning problems. Generally, in PRPs, the impact of competitors has not been considered. Clearly, in the real world, it is no longer possible to have a monopoly market. In competitive environment, customers choose a supplier based on price and quality. So in this article as a definition of quality, providing quick access to customer needs and availability are determined as the requirements of a competitive environment. Therefore, the production routing problem has been modeled with knowing the earliest and latest time of competitor demand meeting. In this way, In case of delay in supplying customers demand, the market share is lost relative to the amount of delay. The problem is modeled and it has been solved by the GAMS software. Since particle swarm optimization has been successfully applied to a variety of problems, here, to solve the problem for the large-sized instances a particle swarm optimization algorithm is also presented. To evaluate the performance of the proposed algorithm, the results with small-sized instances were compared with solutions of GAMS.

کلیدواژه‌ها [English]

  • Production Routing Problem
  • Competitive Environment
  • Particle Swarm Optimization
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