A mixed integer programming method for Pareto front optimization of discrete time cost trade-off problem

Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey

Approval Date: 2015


Supervisor: RİFAT SÖNMEZ


There is a reverse relationship between the activity durations and costs in construction projects. In scheduling of construction projects, the project duration can be compressed (crashed) by expediting some of its activities in several ways including; increasing crew size, working overtime, or using alternative construction methods. As a result, when duration of a critical activity is decreased, its cost increases and project duration decreases. In construction projects, resources are usually available in discrete units. This trade-off between time and cost is named as Discrete Time Cost Trade-off Problem (DTCTP) in literature. DTCTP plays an important role in construction scheduling and especially during schedule acceleration. Inadequate analyses and results for the DTCTP lead to unrealistic project durations and schedule acceleration costs. Hence, development of effective methods for the DTCTP is crucial for not only determination of the right alternative for project costs, but also for setting realistic project duration and budget expectations. However, available software packages do not contain DTCTP analysis which is a drawback. In the literature, there exist both exact and heuristic and meta-heuristic methods to solve DTCTP. However, very few researches have focused on achieving exact solutions for medium and large scale DTCTPs. In this study, a method based on mixed integer programming (MIP) is presented for mainly Pareto front optimization of the medium and large scale DTCTPs. Problem networks are generated to evaluate the performance of the proposed method. The method is mainly developed for Pareto Optimization, however is also tested for single criteria optimization of DTCTP.