The contractor time–cost–credit trade-off problem: integer programming model, heuristic solution, and business insights

Contractors in the construction sector face several trade-offs between time and cost. The time–cost trade-off (TCT) is one of these trade-offs where contractors can reduce a project completion time by assigning more resources to activities, which means spending more money, to shorten the execution times of project activities. On the other hand, contractors who finance their projects through credit lines from banks such that if they reach their credit limits, then the start times of some project activities can be delayed until cash is available again, which might lead to an increase in the project execution time; thus, contractors need to consider the time–credit trade-off. In this work, we simultaneously consider these two trade-offs that affect the project completion time and use mixed integer linear programming (MILP) to model the contractor time–cost–credit trade-off (TCCT) problem. The MILP model minimizes the project execution time given the contractor's budgetary and financial constraints. In addition to the MILP model, we also develop a heuristic solution algorithm to solve the problem. Through a set of benchmark instances, we study the effectiveness of the heuristic algorithm and the computation time of the exact model. It is found that a good upper bound for the MILP results in less computation time. We also study some practical aspects of the problem where we highlight the importance of expediting contractor payments in addition to selecting a financially stable contractor. Finally, we use our MILP model to help a contractor bid for a project.