Minimizing Project Cost by Integrating Subcontractor Selection Decisions with Scheduling

Abstract

Subcontracting has been a worldwide practice in the construction industry. It enables the construction enterprises to focus on their core competences and, at the same time, it makes complex project possible to be delivered. Since general contractors bear full responsibility for the works carried out by their subcontractors, it is their task and their risk to select a right subcontractor for a particular work. Although subcontractor management has been admitted to significantly affect the construction project’s performance, current practices and past research deal with subcontractor management and scheduling separately. The proposed model aims to support subcontracting decisions by integrating subcontractor selection with scheduling to enable the general contractor to select the optimal combination of subcontractors and own crews for all work packages of the project. The model allows for the interactions between the subcontractors and their impacts on the overall project performance in terms of cost and, indirectly, time and quality. The model is intended to be used at the general contractor’s bid preparation stage. The authors claim that the subcontracting decisions should be taken in a two-stage process. The first stage is a prequalification – provision of a short list of capable and reliable subcontractors; this stage is not the focus of the paper. The resulting pool of available resources is divided into two subsets: subcontractors, and general contractor’s in-house crews. Once it has been defined, the next stage is to assign them to the work packages that, bound by fixed precedence constraints, form the project’s network diagram. Each package is possible to be delivered by the general contractor’s crew or some of the potential subcontractors, at a specific time and cost. Particular crews and subcontractors can be contracted more than one package, but not at the same time. Other constraints include the predefined project completion date (the project is not allowed to take longer) and maximum total value of subcontracted work. The problem is modelled as a mixed binary linear program that minimizes project cost. It can be solved using universal solvers (e.g. LINGO, AIMMS, CPLEX, MATLAB and Optimization Toolbox, etc.). However, developing a dedicated decision-support tool would facilitate practical applications. To illustrate the idea of the model, the authors present a numerical example to find the optimal set of resources allocated to a project.