مقایسه کارایی روش های "سیستم کلونی مورچگان" و "برنامه ریزی خطی" در مدل سازی مسأله زمان- بندی تولید جریانی
محورهای موضوعی : مدیریت صنعتی
Said Esfandyari
1
(M.A in Management, Jahad Daneshgahi Higher Education Institute, Yazd Branch)
Ali Morovati Sharif Abadi
2
(Assistant Professor, University of Yazd, Yazd, Iran)
Seyed Habibolah Mirghafouri
3
(Associate Professor, University of Yazd, Yazd, Iran)
Hamid Reza Kadkhodazadeh
4
(M.A in Management, Jahad Daneshgahi Higher Education Institute, Yazd Branch)
کلید واژه: linear programming, برنامه ریزی خطی, زمان بندی, تولید جریانی, الگوریتم سیستم مورچگان, Flow shop scheduling, Ant colony system algorithm,
چکیده مقاله :
هر چند که برنامه ریزی خطی در دنیای واقع کاربردهای زیادی دارد، اما در برخورد با مسائل پیچیده و سخت عدم کارایی خود را نشان داده است. با پیشرفت علم و رویارویی با مشکلات مختلف، تمایل به حل مسائل در حجم زیاد در زمان کوتاه بیشتر شده است. روش های ابتکاری و فوق ابتکاری جدیدترین دستاورد برنامه ریزی غیرخطی در حل این گونه مسائل هستند. یکی از حوزه هایی که نیاز به برنامه ریزی در حجم بالا دارد زمان بندی تولید در مسائل سخت می باشد. این مقاله به مدل سازی و مقایسه دو روش برنامه ریزی خطی و الگوریتم سیستم مورچگان در زمان بندی تولید جریانی منعطف با توجه به متغیرهای تعداد ماشین و سفارش پرداخته است؛ مبنای مقایسه در این پژوهش شاخص های زمان پردازش، تعداد محدودیت، بهینگی و حجم حافظه اشغال شده مربوط به اعداد تصادفی می باشد. در این مقاله از روش پژوهششبه آزمایشی استفاده شده است، ابزار آزمایش به ترتیب نرم افزارهای سی شارپ و لینگو برای الگوریتم مورچگان و برنامه ریزی خطی است. نتایج به دست آمده نشان می دهد که مدل برنامه ریزی خطی درتعداد ماشین و سفارش پایین کارایی بالاتری دارد، اما با افزایش ماشین و سفارش با توجه به شاخص های در نظر گرفته شده، الگوریتم سیستم مورچگان کارایی بالاتر خود را نشان می دهد.
Although linear programming is used widely in the world, its inefficiency in dealing with difficult problems is concerned. With the advancement in science and dealing with various problems, it tends to have problems in mass production in a short time. Heuristic and meta-heuristic techniques are the latest achievements of nonlinear programming for solving the similar problem. One area that requires programming applications in mass production is NP-scheduling problems. This paper aims at modeling and comparing the two methods of Linear Programming and Ant Colony System Algorithm in flexible flow shop scheduling problem according to the number of jobs and machines. This study is based on comparing the index of time processing, the number of constraints, optimality, and the memory size of the random numbers. Using Quasi-experimental research method, software testing tools are C-sharp and Lingo for the ant colony algorithm and linear programming respectively. The results show that linear programming model has higher performance when machines and jobs are in low numbers; however, with the rise of the machines and jobs, Ant Colony System algorithm has proven high efficiency.
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