Abstract

A genetic algorithm (GA)-based model to deal with time-cost trade-off problems is presented. The traditional algorithms assume the unlimited availability of resources. Instead, the proposed model allows for resource constraints. Accordingly, the trade-off is considered in terms of the level of resources to be deployed for each activity. At the same time the model schedules the starts of the activities in order to optimize the objective function. The activity starts is a significant factor in the case of non-uniform available profile. The GA searches both spaces of resource utilization and activity starts to determine the optimal schedule that conforms to the resource available profile. Although, in principle, this has the potential of a combinatorial explosion, earlier work suggests that the GA-based model can be applied to larger networks without appearing to suffer from this problem. Allowing the project manager to think in terms of resource utilization makes this approach consistent with resource allocation problems, and more pragmatic and appealing. The model can also be used to solve conventional time-cost trade-off problems by a simple modification of the objective function. Numerical examples are used to illustrate the working of the model. The examples include a case of varying resource available profile.

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