Scheduling of Repetitive Projects with Cost Optimization

Abstract

Existing dynamic programming formulations are capable of identifying, from a set of possible alternatives, the optimum crew size for each activity in a repetitive project. The optimization criterion of these formulations is, however, limited to the minimization of the overall duration of the project. While this may lead to the minimization of the indirect cost of the project, it does not guarantee its overall minimum cost. The objective of this paper is to present a model that incorporates cost as an important decision variable in the optimization process. The model utilizes dynamic programming and performs the solution in two stages: first a forward process to identify local minimum conditions, and then a backward process to ensure an overall minimum state. In the first stage, a process similar to that used in time‐cost trade‐off analysis is employed, and a simple scanning and selecting process is used in the second stage. An example project from the literature is analyzed in order to demonstrate the use of the model and its validity, and illustrate the significance of cost as a decision variable in the optimization process.