A review of the recent literature on the models that focus on resource leveling in Critical Path Method networks shows that different objective functions have been used to optimize resource utilization. The main objective of this study is to investigate the impacts of using different objective functions on resource utilization histograms in Critical Path Method networks. For this purpose, nine different resource leveling objective functions were optimized via a genetic algorithm-based model. The model was developed using actual data obtained from a steel framed industrial building construction project. It was found that each of these objective functions generates different resource utilization histograms. In order to determine the improvement levels achieved by resource leveling using nine different objective functions, the improvement percentage in each parameter and the average improvement percentage for each objective function were calculated. Even though the objective function that involves the minimization of the sum of the square of the deviations in daily resource usage provided the best average improvement percentage in the studied case, another objective function(s) may provide better average improvement percentage in different projects. The contractor should consider all objective functions for resource leveling and select the one(s) that provides the best average improvement percentage.
Unbalanced bidding is a common practice used in both unit price and lump sum contracts. Contractors may unbalance their bids in different forms for various reasons. The studies in the literature either focus on developing optimization models that assist contractors in winning contracts and maximizing profits of their bids through unbalancing or developing models that assist owners in detecting and/or preventing unbalanced bids during the bid evaluation stage. Unbalanced bidding is one of the most controversial subjects in the construction management literature and practice. Although there is no consensus on whether it is unethical or not, this practice is not usually for the benefit of owners. Therefore, owners have the right to reject the unbalanced bids and create a fair competition environment if they have a mechanism to detect it during the bid evaluation process. The main objective of this study is to propose a model, which consists of five different grading systems and helps owners in detecting unbalanced bids during the tendering process. In the proposed model, owners may either calculate the individual grades of each bidder or calculate the final score of each bidder by assigning different weights to these grading systems according to the project characteristics or their own needs. The final scores and bid prices of the contractors can be simultaneously evaluated. In order to demonstrate the applicability of the proposed model, an illustrative example is presented. It can be concluded that the proposed model can be effectively and easily used by owners for detecting unbalanced bids. This paper is the revised version of the paper that has been published in the proceedings of the Creative Construction Conference 2018 (Polat et al., 2018).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.