Solving the Resource-Constrained Project Scheduling Problem by Genetic Algorithm(<Special English Issue>Global Supply Chain Management)

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概要

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• The resource-constrained project scheduling problem (RCPSP) is one of the most difficult challenges in project schedule management. In the previous research work for RCPSP, activity durations in the project are often initially determined by the fixed values (fixed activity durations), and then the optimization process is carried out to assign the optimal start times of activities. In many cases, however, the activity durations vary within the certain ranges (variable activity durations), and depend on the scheduling objective. Thus, it is highly probable that these initially fixed activity durations lead to unexpected results. The way in which the activity durations are reasonably assigned is very important for reducing the overall project duration under resource constraints. For solving the RCPSP with variable activity durations, it is impossible to use the traditional methods (such as CPM, PERT), so the new method based on genetic algorithm (GA) is proposed in this paper for solving the problem. In the proposed method, the genetic algorithm is introduced to determine the optimal activity durations, and the heuristic rules are applied to assign the optimal start time of each activity so that the overall project duration under resource constraints is minimized.

• 社団法人日本経営工学会の論文
• 2007-02-15

著者

• Long Luong

  Graduate School of Engineering, Nagaoka University of Technology

• Ohsato Ario

  Department of Management and Information Systems Science, Nagaoka University of Technology

• Ohsato Ario

  Department Of Management And Information Systems Science Nagaoka University Of Technology

• Ohsato Ario

  Department Of Electrical Engineering Faculty Of Engineering Yokohama National University

• Long Luong

  Graduate School Of Engineering Nagaoka University Of Technology

関連論文

• Linear Solution Method for Aggregate Production Planning with Fuzzy Goals
• Satisfactory Efficient Linear Coordination Method forMulti-Objective Linear Programming Problems withConvex Polyhedral Preference Functions
• Project Schedule Management Using a Fuzzy Activity Network Considering Resource and Environmental Factors
• Solving the Resource-Constrained Project Scheduling Problem by Genetic Algorithm(Global Supply Chain Management)
• Satisfactory Efficient Linear Coordination Method for Multi-Objective Linear Programming Problems with Convex Polyhedral Preference Functions
• Expected Time without Failure for a Year

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