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Dual-objective Preemptive Multi-mode Resource-Constrained Project Scheduling Problem Optimization Model | ||
| Advances in Industrial Engineering | ||
| مقاله 4، دوره 51، شماره 1، تیر 2017، صفحه 29-44 اصل مقاله (1.19 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jieng.2017.61892 | ||
| نویسندگان | ||
| Hamzeh Amin-Tahmasbi* 1؛ Allahyar Daghbandan2؛ Roya Bagherpour3 | ||
| 1Department of Industrial Engineering, Faculty of Technology and Engineering, University of Guilan, Iran | ||
| 2Department of Chemical Engineering, Faculty of Technology and Engineering, University of Guilan, Iran | ||
| 3Department of Industrial Engineering, Kooshyar Higher Educational Institute, Rasht, Iran | ||
| چکیده | ||
| The Multi-Mode Resource Constrains Project Scheduling Problem (MRCPSP) tries to find the best sequence of activities in a manner that involves more than one type of operating mode and in the presence of resource constraints, project’s precedence constraints must be satisfied. In each execution mode, the amount of resources and execution time are specified and different. In The Preemptive multi-mode Resource Constraints Project Scheduling Problem (P-MRCPSP), each operating mode activity can be interrupted and restarted at any time without any extra cost. In this paper, minimizing the completion time along with maximizing the current net value of the project in the P-MRCPSP are considered. After solving the problem by using Epsilon limits method, according to NP-hard problem and multi-objective model, multi-objective particle swarm optimization (MOPSO) has been developed to achieve optimum scheduling. In order to evaluate the proposed method’s efficiency, results have been compared to non-dominance genetic algorithm sorting (NSGAII) based on designed indicators. The Taguchi method has been used in experimental design, to adjust these two algorithms’ parameters. The results of the model solution show the strength of MOPSO algorithm. | ||
| کلیدواژه‌ها | ||
| Cessation of activities؛ meta-heuristic methods؛ Multi-mode execution؛ Multi-objectives particle swarm algorithm؛ Resources-constrained project scheduling | ||
| عنوان مقاله [English] | ||
| بهینه‌سازی مدل دوهدفۀ مسئلۀ زمان‌بندی پروژه با منابع محدود باوجود چند حالت اجرایی و امکان قطع فعالیت‌ها | ||
| نویسندگان [English] | ||
| حمزه امین طهماسبی1؛ الهیار داغبندان2؛ رویا باقرپور3 | ||
| 1استادیار گروه مهندسی صنایع دانشکدة فنی و مهندسی شرق، دانشگاه گیلان | ||
| 2استادیار گروه مهندسی شیمی دانشکدة فنی، دانشگاه گیلان | ||
| 3دانشجوی کارشناسی ارشد مهندسی صنایع مؤسسۀ آمـوزش عـالی کوشیـار رشـت | ||
| چکیده [English] | ||
| مسئلة زمان‌بندی پروژه با منابع محدود با وجود چند حالت اجرایی (MRCPSP) ، به‌دنبال یافتن بهترین توالی انجام‌دادن فعالیت‌هاست، به‌نحوی‌که با وجود انواع محدودیت منابع، باید محدودیت‌های تقدم و تأخر پروژه ارضا شود و فعالیت‌ها نیز بیش از یک نوع حالت اجرایی داشته باشند. در هریک از این حالت‌های اجرایی، مقدار منابع و زمان اجرایی فعالیت‌ها مشخص و متفاوت است. در مسئلة زمان‌بندی پروژه با منابع محدود و چند حالت اجرایی با امکان قطع فعالیت‌ها (P-MRCPSP)، فعالیت‌ها می‌توانند در هر حالت اجرایی قطع و در هر زمانی بدون اضافه‌شدن هزینه دوباره شروع شوند. در این پژوهش کمینه‌ساختن زمان تکمیل پروژه در کنار بیشینه‌سازی ارزش خالص فعلی پروژه در مسئله P-MRCPSP مدنظر قرار گرفته است. پس از حل مسئله با استفاده از روش محدودیت اپسیلون، با توجه به NP-hard بودن مسئله و چندهدفه‌بودن مدل، الگوریتم تکاملی چندهدفة بهینه‌سازی ازدحام ذرات (MOPSO) برای دستیابی به زمان‌بندی بهینه توسعه داده شده است. به‌منظور ارزیابی کارایی روش پیشنهادی، نتایج براساس شاخص‌های طراحی‌شده با الگوریتم ژنتیک مرتب‌سازی نامغلوب (NSGAII) مقایسه می‌شود. برای تنظیم پارامترهای دو الگوریتم از روش تاگوچی در طراحی آزمایش‌ها استفاده شده است. نتایج حل مدل نشان‌دهندة قوت الگوریتم MOPSO است. | ||
| کلیدواژه‌ها [English] | ||
| الگوریتم چندهدفه ازدحام ذرات, تعدد حالات اجرایی, روش‌های فرا ابتکاری, زمان‌بندی پروژه با منابع محدود, قطع فعالیت | ||
| مراجع | ||
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