زمان‌بندی سیستم جریان کارگاهی با محدودیت دسترسی ماشین و اثر یادگیری مبتنی بر یک مدل ترکیبی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، دانشگاه شهید بهشتی.

2 کارشناسی ارشد، موسسه آموزش عالی رجا.

چکیده

در طول دهه‌های اخیر مسئله زمان‌بندی سیستم جریان کارگاهی با مفروضات مختلفی بررسی شده است. یکی از حالاتی که توجه بسیاری از پژوهشگران را به خود جلب کرده است، در نظرگیری مفهوم یادگیری است. در شرایط واقعی محیط‌های کاری، اثر یادگیری تنها به موقعیت کارها محدود نمی‌شود؛ به‌عبارت‌دیگر تجربه کارگران نیز در طول روند عملیات باید در نظر گرفته شود. از طرف دیگر عوامل زیادی سبب در‌دسترس‌نبودن ماشین‌آلات و تجهیزات در افق برنامه‌ریزی می‌شود. این پژوهش یک مسئله جریان کارگاهی با محدودیت دسترسی ماشین و اثر یادگیری مبتنی بر یک مدل ترکیبی را موردمطالعه قرار می‌دهد. این مدل یادگیری به‌طور همزمان مبتنی بر موقعیت کارها و همچنین مجموع لگاریتمی زمان پردازش کارها است. در ابتدا یک مدل برنامه‌ریزی مختلط عدد صحیح برای مسئله ارائه و سپس به دلیل پیچیدگی بالای مدل، از دو الگوریتم فرا ابتکاری شبیه‌سازی تبرید (SA) و شبیه‌سازی تبرید مبتنی بر نظریه ابر (CSA)، برای یافتن جواب‌های نزدیک به بهینه استفاده شده است. تحلیل نتایج حاکی از آن است که عملکرد الگوریتم CSA به‌طور معنا‌داری بالاتر از عملکرد الگوریتم SAاست. 

کلیدواژه‌ها

عنوان مقاله [English]

Flow Shop Scheduling Problem with Machine Availability Constraints and Learning Effect based on a Hybrid Model

نویسندگان [English]

  • Mostafa Zandieh 1
  • Azadeh Fotovat 2
1 Associate Professor, Shahid Beheshti University.
2 M.Sc., Raja Institute of Higher Education.
چکیده [English]

During the recent decades, flow shop scheduling problem has investigated with different assumptions. One of the most important one that has attracted many researchers, is consideration the concept of learning effect. In real situation of work environment, learning effect is not limited to job position, in other word, workers experiments also should be considered during the process of operations. In one hand, there are factors that can cause machines and equipment unavailability in the planning horizon. This study investigates flow shop scheduling problem with machine availability constraints and learning effect based on a hybrid model. This learning model includes not only job positions but also total logarithmic processing time of jobs. First, a mixed integer liner programming model has been proposed to formulate the problem. Because of high complexity of this model, two meta-heuristic algorithms, simulated annealing (SA) and cloud theory-based simulated annealing (CSA) have been used to find nearly optimal solutions. Finally it is cleared that, CSA could be more successful in generating nearly optimal solutions than SA.

کلیدواژه‌ها [English]

  • Scheduling
  • Flow Shop
  • Learning Effect based on a Hybrid model
  • Machine Availability Constraint
  • Cloud Theory-based Simulated Annealing Algorithm

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