Towards competitive contractors' bids: Optimizing selections of subcontractors and payment lags using branch and bound algorithm

Contractors are constantly looking for methods to lower bid prices and enhance competitiveness. This paper presents a method for conducting negotiations between the contractor and subcontractors, wherein the contractor requests subsidized prices from subcontractors in exchange for making their payments before collecting owner's payments. While the prompt payments lower the financing needs and costs for subcontractors, the contractor's financing needs and costs are raised. The trade-off between the contractor's increased financing costs and subcontractors' subsidized prices ultimately determines the optimum contractor's bid price. In this paper, the branch and bound (B&B) algorithm is used to determine the minimum contractor's bid price, including financing costs. This is accomplished through making the best assignments of the prospective subcontractors to the outsourced works along with determining their payment lags. Four different search methods are designed and used for the B&B algorithm to solve small and large-size problems. Through benchmarking against the exhaustive enumeration, the results proved that the B&B algorithm explored the problems' search spaces while implementing pruning rules effectively to obtain the optimum solutions within a less computational time.