Seyed Mohsen Shahandashti

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a r t i c l e i n f o Since scheduling of multiple projects is a complex and time-consuming task, a large number of heuristic rules have been proposed by researchers for such problems. However, each of these rules is usually appropriate for only one specific type of problem. In view of this, a hybrid of genetic algorithm and simulated annealing (GA-SA(More)
Project managers need to assess how well construction crews are performing in terms of productivity. This paper presents the preliminary results of an effort carried out by the authors to develop a simulation based framework to support the identification of the information requirements for assessing productivity performance. A prototype to test the proposed(More)
This paper integrates multi-project scheduling and linear scheduling concepts. Since the problem is combinatorial, a two-stage heuristic solution-finding procedure is used to model the problem with multiple resource constraints. Simulated annealing is utilized as a searching engine in the second stage to find the probable optimized solution. The first stage(More)
Project managers need to assess how well construction crews are performing in terms of productivity. This paper presents the preliminary results of an effort carried out by the authors to develop a simulation based framework to support the identification of the information requirements for assessing productivity performance. A prototype to test the proposed(More)
This paper proposes a new algorithm using Simulated Annealing (SA) for stochastic scheduling. Stochastic effects are added with nondeterministic activity durations. Simple simulated annealing can not properly handle such a complex problem so an improved version is produced and utilized within the algorithm. Generally, the availability of resources is not(More)
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