TY - GEN

T1 - A random key-based genetic algorithm approach for resource-constrained project scheduling problem with multiple modes

AU - Okada, I.

AU - Zhang, X. F.

AU - Yang, H. Y.

AU - Fujimura, S.

PY - 2010/12/1

Y1 - 2010/12/1

N2 - In the practice of scheduling of construction projects, there is a great variety of methods and procedures that need to be selected at each construction process during project. Accordingly, it is important to consider the different modes that may be selected for an activity in the scheduling of construction projects. In this study, first, we mathematically formulate the resource-constrained project scheduling problem with multiple modes while minimizing the total project time as the objective function. Following, we propose a new random key-based genetic algorithm approach which includes the mode reduction procedures to solve this NP-hard optimization problem. Finally, in order to evaluate the performance of our method, we are scheduled in the close future to implement the proposed approach on some standard project instances as the computational experiment and analyze these experimental results comparing with the bi-population-based genetic algorithm by Peteghem and Vanhoucke [1].

AB - In the practice of scheduling of construction projects, there is a great variety of methods and procedures that need to be selected at each construction process during project. Accordingly, it is important to consider the different modes that may be selected for an activity in the scheduling of construction projects. In this study, first, we mathematically formulate the resource-constrained project scheduling problem with multiple modes while minimizing the total project time as the objective function. Following, we propose a new random key-based genetic algorithm approach which includes the mode reduction procedures to solve this NP-hard optimization problem. Finally, in order to evaluate the performance of our method, we are scheduled in the close future to implement the proposed approach on some standard project instances as the computational experiment and analyze these experimental results comparing with the bi-population-based genetic algorithm by Peteghem and Vanhoucke [1].

KW - Bi-population-based genetic algorithm

KW - Makespan

KW - Random key-based genetic algorithm

KW - Resource-constrained project scheduling problem

UR - http://www.scopus.com/inward/record.url?scp=79952379072&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79952379072&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:79952379072

SN - 9789881701282

T3 - Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010

SP - 106

EP - 111

BT - Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010

T2 - International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010

Y2 - 17 March 2010 through 19 March 2010

ER -