Mixed-Integer Nonlinear Programming Model for Nonlinear Discrete Optimization of Project Schedules under Restricted Costs

Abstract

This paper presents the mixed-integer nonlinear programming (MINLP) model for nonlinear discrete optimization of project schedules under restricted costs. The proposed model includes cost-objective function, generalized precedence relationship constraints, project duration restraints, logical conditions, and cost restrictions. The MINLP model allows inclusion of a wide variety of nonlinear expressions and provides the exact optimal output data for construction project management, such as a Gantt chart, histogram, and S-curve of total project cost. The novelty of the contribution is that the planner is now enabled to perform the exact optimal scheduling of project activities simultaneously with scheduling of nonlinearly restricted total project cost at each discrete working time unit. At this point, the restrictions can be set on increments and cumulative values of total project cost. A set of application examples is shown in this paper to demonstrate the advantages of the proposed model.