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A discrete-time approximation technique for the time-cost trade-off in PERT networks

Published online by Cambridge University Press:  15 June 2007

Amir Azaron ,
Masatoshi Sakawa ,
Reza Tavakkoli-Moghaddam  and
Nima Safaei
Amir Azaron
Affiliation:
Department of Industrial Engineering, Dalhousie University, Halifax, Nova Scotia, B3J 2X4 Canada; a.azaron@dal.ca
Masatoshi Sakawa
Affiliation:
Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, Kagamiyama 1-4-1, Higashi-Hiroshima, Hiroshima, 739-8527 Japan; sakawa@msl.sys.hiroshima-u.ac.jp
Reza Tavakkoli-Moghaddam
Affiliation:
Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran; tavakoli@ut.ac.ir
Nima Safaei
Affiliation:
Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran; nimasafaei@iust.ac.ir
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Abstract


We develop a discrete-time approximation technique dealing with the time-cost trade-off problem in PERT networks. It is assumed that the activity durations are independent random variables with generalized Erlang distributions, in which the mean duration of each activity is a non-increasing function of the amount of resource allocated to it. It is also assumed that the amount of resource allocated to each activity is controllable. Then, we construct an optimal control problem with three conflicting objective functions. Solving this optimal control problem, optimally, is impossible. Therefore, a discrete-time approximation technique is applied to solve the original multi-objective optimal control problem, using goal attainment method. To show the advantages of the proposed technique, we also develop a Simulated Annealing (SA) algorithm to solve the problem, and compare the discrete-time approximation results against the SA and also the genetic algorithm results.

Keywords

Project managementmultiple objective programmingoptimal controlmarkov processessimulated annealing.
Type
Research Article
Information
RAIRO - Operations Research , Volume 41 , Issue 1 , January 2007 , pp. 61 - 81
Copyright
© EDP Sciences, ROADEF, SMAI, 2007

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