نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، دانشگاه اصفهان.

2 استادیار، دانشگاه اصفهان.

چکیده

در این مقاله با هدف حداکثر‌کردن ارزش فعلی خالص و در‌نظر‌گرفتن شیوه‌های مختلف پرداخت کارفرما، مسئله انتخاب و زمان‌بندی چندین پروژه با استفاده از برنامه‌ریزی ریاضی و برنامه‌ریزی محدودیتی بررسی شده است؛ به‌طوری‌که امکان‌پذیری پروژه‌ها با توجه به میزان منابع در‌دسترس تضمین و کلیه روابط پیش‌نیازی رعایت شود. فعالیت‌ها با حالت مختلف از منابع، امکان اجرا دارند و از منابع تجدیدپذیر (نیروی انسانی، ماشین‌آلات) و تجدیدناپذیر (مواد اولیه، بودجه) استفاده می‌کنند. در محاسبه هزینه‌ها، هزینه اضافه‌کاری منابع تجدید‌پذیر، جریمه دیرکرد یا پاداش تحویل زودتر از موعد پروژه در نظر گرفته شده است. مدل‌های ایجادشده با چند پروژه از کتابخانه‌های مسائل زمان‌بندی پروژه بررسی شده‌اند.

کلیدواژه‌ها

عنوان مقاله [English]

Multi-Mode Resource Constrained Multi-Project Selecting and Scheduling Problem to Maximize Net Present Value

نویسندگان [English]

  • Omid Movahedian Attar 1
  • Majid Esmaelian 2
  • Dariush Mohammadi Zanjirani 2

1 MSc. Student, Isfahan University.

2 Assistant Professor, Isfahan University.

چکیده [English]

In this article, with the aim of maximizing net present value and considering various ways of the payment, the problem of selecting and scheduling several projects using mathematical programming and constraint programming have been investigated, in a way that the project feasibility with regards to the level of available resources is guaranteed and all of the prerequisite relationships are observed. Activities with the different modes of resources can be done. They uses renewable (human resources, equipment) and non-renewable (raw materials, budgets) resources. In calculating the costs, the overtime cost of renewable resources, late penalties or rewards of delivery before the project due date is considered. Created Models are tested by a number of projects from the PSPLIB libraries.

کلیدواژه‌ها [English]

  • Constraint Programming
  • Mathematical Modeling
  • Net Present Value
  • Project Scheduling
  • Project Selection
 
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