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contributor authorمنصور قلعه نویen
contributor authorMansour Ghalehnovifa
date accessioned2020-06-06T13:08:14Z
date available2020-06-06T13:08:14Z
date issued2012
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/3343002?show=full
description abstractIn order to perform a project, all project managers are facing with high quality standards and benefiting from shortest period of time, possible resources and continuous fights. There are a lot of social and economic factors for a project manager to have an optimized benefit from limited accessible resources either from man power point of view or reserve of materials. Various tools and several techniques are introduced within recent decades for scheduling of projects, but most of them are involved with scheduling of single projects and least for multi-projects. We can model different Courses of Action (COAs) evaluated during the operational military planning as many different activity networks. The corresponding project scheduling model is sufficiently general to be able to represent the most part of military missions. Recently, a project scheduling mathematical model has

been proposed where each activity called an action in the military context has different execution modes depending on the resource combination selected. This paper is a combination of Simulated Annealing Algorithm and the best Priority rules for solving the problem of scheduling in multi projects with limited resources that has been tested with numerical examples. The numerical tests make it clear that proposed method is better than multi-applicable rules of scheduling.
en
languageEnglish
titleMulti-Projects Scheduling with Resource Constraints and Priority Rules and Fuzzy Activitiesen
typeJournal Paper
contenttypeExternal Fulltext
subject keywordsRCMPSPen
subject keywordsschedulingen
subject keywordssimulated annealing algorithmen
subject keywordspriority rulesen
journal titleTexas Journal of Sciencefa
pages543-553
journal volume23
journal issue3
identifier linkhttps://profdoc.um.ac.ir/paper-abstract-1028092.html
identifier articleid1028092


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