Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Resource Pool Location for Periodic Services in Decentralized Multi-Project Scheduling Problems
Going through the literature of multi-project scheduling problems reveals that the resources required for the completion of each activity need to move among other activities without spending time and money. Recently, the literature has been mainly concentrated on resource transfer among the activities for decentralized multi-project scheduling problems. Determining the best location of facilities for periodic services is one of the main points in the decentralized multi-projects scheduling problem. Indeed, discovering the best known location can reduce the project completion time, in particular for those projects in which the activities are far from each other and also activity’s execution takes significant time. This article introduces a novel decentralized resource-constrained multi-project scheduling problem considering periodic services. The purpose of this problem is to minimize the cost associated with the project’s completion times (at the operational level) and the construction cost of resource pool (at the strategic level) at the same time. First, for better illustration of the problem under consideration, a mixed-integer linear programming model is presented, which efficiently solves small-size problems in a reasonable time. Then, a fast priority rule-based constructive heuristic algorithm is originally introduced. Finally, by incorporating the proposed heuristic structure, a combinatorial artificial bee colony (CABC) algorithm is developed to solve such large-size problems efficiently. To evaluate the modeling procedures, the computational results and managerial insights on test problems are presented. The results reveal that in decentralized multi-project scheduling problems, by considering the resource pool’s location the total costs will be reduced. Numerical investigations indicate that the proposed CABC algorithm yields the best known solutions with an average relative gap of 2.5% for large-size instances.
Resource Pool Location for Periodic Services in Decentralized Multi-Project Scheduling Problems
Going through the literature of multi-project scheduling problems reveals that the resources required for the completion of each activity need to move among other activities without spending time and money. Recently, the literature has been mainly concentrated on resource transfer among the activities for decentralized multi-project scheduling problems. Determining the best location of facilities for periodic services is one of the main points in the decentralized multi-projects scheduling problem. Indeed, discovering the best known location can reduce the project completion time, in particular for those projects in which the activities are far from each other and also activity’s execution takes significant time. This article introduces a novel decentralized resource-constrained multi-project scheduling problem considering periodic services. The purpose of this problem is to minimize the cost associated with the project’s completion times (at the operational level) and the construction cost of resource pool (at the strategic level) at the same time. First, for better illustration of the problem under consideration, a mixed-integer linear programming model is presented, which efficiently solves small-size problems in a reasonable time. Then, a fast priority rule-based constructive heuristic algorithm is originally introduced. Finally, by incorporating the proposed heuristic structure, a combinatorial artificial bee colony (CABC) algorithm is developed to solve such large-size problems efficiently. To evaluate the modeling procedures, the computational results and managerial insights on test problems are presented. The results reveal that in decentralized multi-project scheduling problems, by considering the resource pool’s location the total costs will be reduced. Numerical investigations indicate that the proposed CABC algorithm yields the best known solutions with an average relative gap of 2.5% for large-size instances.
Resource Pool Location for Periodic Services in Decentralized Multi-Project Scheduling Problems
Rostami, Mohammad (Autor:in) / Bagherpour, Morteza (Autor:in) / Mazdeh, Mohammad Mahdavi (Autor:in) / Makui, Ahmad (Autor:in)
09.03.2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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