Optimization-based Approach for Organizing the Bidding of Nonserial Repetitive Projects

In practice, the number of contracts and the categories of contractors to be called for bidding on nonserial repetitive projects under one major program often are estimated on the basis of intuition and experience. It may involve emotional reactions to existing surrounding conditions. Accordingly, the factors that form the possible different scenarios should be properly analyzed and evaluated. This paper introduces an analytical model that allows for decisions on the number of contracts and projects per contractor for different contractor categories within major construction infrastructure programs. These optimum decisions are reached using an integrated time and cost objective. Genetic algorithm has been employed for performing optimization. A computer-based model has been developed and validated.