حل مساله زمانبندی پروژه در حالت پایدار با محدودیت منابع و موعد تحویل بازه ای
محورهای موضوعی : مدیریت صنعتی
میثم جعفری اسکندری
1
(دانشگاه پیام نور تهران)
روزبه عزیزمحمدی
2
(دانشگاه پیام نور)
کلید واژه: زمان بندی پروژه با محدودیت منابع, زمانبندی پایدار, انقطاع فعالیت, موعد تحویل فعالیت, جریمه دیرکرد و زودکرد, الگوریتم NSGA ll, الگوریتم فاخته, ,
چکیده مقاله :
مسئله زمانبندی پروژه در حالت چند وضعیتی با محدودیت منابع یکی از مسایل زمانبندی می باشد که مورد توجه محققان در سال های اخیر به دلایل راهبردی و کاربردی بودن این مسایل در ابعاد عملی و تئوری قرار گرفته است. در این پژوهش زمانبندی پروژه در حالت محدودیت منابع از هر دو نوع تجدیدپذیر و تجدید ناپذیر ضمن اینکه به دنبال کمینه کردن زمان و هزینه های اتمام پروژه که برگرفته از هزینه های متاثر از زمان تحویل فعالیت ها و منابع مصرفی می باشد به دنبال افزایش پایداری شبکه زمانبندی پروژه نیز می باشد تا با بهینه شدن زمان و هزینه پروژه فعالیت ها نیز با بیشترین پایداری ممکن برنامه ریزی و اجرا شوند. این مدل های ریاضی از نوع مسایل NP-Hard (دمیولمستر و هرلن، 2002) به حساب می آید و برای حل آن از الگوریتم های فراابتکاری از جمله ژنتیک2 و الگوریتم فاخته استفاده شده است و با آزمایشات تاگوچی به عنوان یک روش بهینه سازی آماری برای تنظیم پارامتر های ژنتیک2 و فاخته مورد استفاده قرار گرفته و سپس الگوریتم های مورد اشاره با استفاده از آزمون t با یکدیگر مقایسه و نتایج آن مورد بحث و تصمیم گیری قرار گرفته است
Due to considering the real conditions of project and solving manager’s problems, the primary methods development of scheduling for projects has recently drawn researcher’s attentions so that these methods are looking for finding optimal sequence to realize project goals and to provide its constraints such as dependence, resource constraint (renewable and non-renewable). The importance of these issues has practically and theoretically led researchers to do much efforts on different conditions of issues for project schedule, various methods to solve and or to develop each of them. In this research based on selection of some executive methods for any activity with renewable and non-renewable resource and considering prerequisite relation from kind of start to end and having delivery time for any activity in two time periods that has been provided with regard to delivery time of penalty cost with delay or without delay. The presented model has been solved in small scale by gams software and in small, medium and large scale using meta-heuristic Methods of NSGA ll and cuckoo after coding in software of matlab 2013. The comparison of the answer obtained from the above algorithm indicates the better performance of genetic algorithm in most indexes and cuckoo algorithm has superiority on time index of problem solving.
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