An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems
In this paper a novel modelling and solving method has been developed to address the so-called resource constrained project scheduling problem (RCPSP) where project tasks have multiple modes and also the preemption of activities are allowed. To solve this NP-hard problem, a new general optimization...
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doaj-0009ce24e5a24dcdae8a879c55e9a6b92020-11-24T21:17:40ZengIran University of Science & TechnologyInternational Journal of Industrial Engineering and Production Research2008-48892345-363X2017-11-01284429439An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problemsParham Azimi0Naeim Azouji1 Qazvin Islamic Azad University Qazvin Islamic Azad University In this paper a novel modelling and solving method has been developed to address the so-called resource constrained project scheduling problem (RCPSP) where project tasks have multiple modes and also the preemption of activities are allowed. To solve this NP-hard problem, a new general optimization via simulation (OvS) approach has been developed which is the main contribution of the current research. In this approach, the mathematical model of the main problem is relaxed and solved then the optimum solutions were used in the corresponding simulation model to produce several random feasible solutions for the main problem. Finally, the most promising solutions were selected as the initial population of a genetic Algorithm (GA). To test the efficiency of the problem, several test problems were solved by the proposed approach and according to the results, the proposed concept has a very good performance to solve such a complex combinatoral problem. Also, the concept could be easily applied for other similar combinatorics. http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-630-2&slc_lang=en&sid=1Optimization via Simulation Multi-mode Resource Constraint Project Scheduling Problem Genetic Algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Parham Azimi Naeim Azouji |
spellingShingle |
Parham Azimi Naeim Azouji An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems International Journal of Industrial Engineering and Production Research Optimization via Simulation Multi-mode Resource Constraint Project Scheduling Problem Genetic Algorithm |
author_facet |
Parham Azimi Naeim Azouji |
author_sort |
Parham Azimi |
title |
An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems |
title_short |
An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems |
title_full |
An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems |
title_fullStr |
An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems |
title_full_unstemmed |
An Optimization via Simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems |
title_sort |
optimization via simulation approach for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problems |
publisher |
Iran University of Science & Technology |
series |
International Journal of Industrial Engineering and Production Research |
issn |
2008-4889 2345-363X |
publishDate |
2017-11-01 |
description |
In this paper a novel modelling and solving method has been developed to address the so-called resource constrained project scheduling problem (RCPSP) where project tasks have multiple modes and also the preemption of activities are allowed. To solve this NP-hard problem, a new general optimization via simulation (OvS) approach has been developed which is the main contribution of the current research. In this approach, the mathematical model of the main problem is relaxed and solved then the optimum solutions were used in the corresponding simulation model to produce several random feasible solutions for the main problem. Finally, the most promising solutions were selected as the initial population of a genetic Algorithm (GA). To test the efficiency of the problem, several test problems were solved by the proposed approach and according to the results, the proposed concept has a very good performance to solve such a complex combinatoral problem. Also, the concept could be easily applied for other similar combinatorics. |
topic |
Optimization via Simulation Multi-mode Resource Constraint Project Scheduling Problem Genetic Algorithm |
url |
http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-630-2&slc_lang=en&sid=1 |
work_keys_str_mv |
AT parhamazimi anoptimizationviasimulationapproachforthepreemptiveandnonpreemptivemultimoderesourceconstrainedprojectschedulingproblems AT naeimazouji anoptimizationviasimulationapproachforthepreemptiveandnonpreemptivemultimoderesourceconstrainedprojectschedulingproblems AT parhamazimi optimizationviasimulationapproachforthepreemptiveandnonpreemptivemultimoderesourceconstrainedprojectschedulingproblems AT naeimazouji optimizationviasimulationapproachforthepreemptiveandnonpreemptivemultimoderesourceconstrainedprojectschedulingproblems |
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1726012803733520384 |