Project schedule compression: a multi-objective methodology

Abstract

Purpose -This paper aims to present a new method to circumvent the limitations of current schedule compression methods which reduce schedule crashing to the traditional time-cost trade-off analysis, where only cost is considered. Design/methodology/approach -The schedule compression process is modeled as a multi-attributed decision making problem in which different factors contribute to priority setting for activity crashing. For this purpose, a modified format of the Multiple Binary Decision Method (MBDM) along with iterative crashing process is utilized. The method is implemented in MATLAB, with a dynamic link to MS-Project to facilitate the needed iterative rescheduling. To demonstrate the use of the developed method and to present its capabilities, a numerical example drawn from literature was analysed. Findings -When considering cost only, the generated results were in good agreement with those generated using the harmony search (HS) method, particularly in capturing the project least-cost duration. However, when other factors in addition to cost were considered, as expected, different project least-cost and associated durations were obtained.Research limitations/implications -The developed method is not applicable, in its present formulation, to what is known as "linear projects" such as construction of highways and pipeline infrastructure projects which exhibit high degree of repetitive construction. Originality/value -The novelty of the developed method lies in its capacity to allow for the consideration of a number of factors in addition to cost in performing schedule compression. Also through its allowance for possible variations in the relative importance of these factors at the individual activity level, it provides contractors with flexibility to consider a number of compression execution plans and identifies the most suitable plan. Accordingly, it enables the integration of contractors' judgment and experience in the crashing process and permits consideration of different project environments and constraints.

A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling

“…In their study, Moselhi and Roofigari-Esfahan [37] used MATLAB with a dynamic link to MS Project for the purpose of solving the multi-objective TCTP. The authors employed the HS method that tends to find the best set of project activity alternatives through the generation of harmony memory matrix and updating this matrix by replacing each activity's alternative with one that better satisfies the objective of gaining less total project cost.…”

An evolutionary stochastic discrete time-cost trade-off method

“…Furthermore, fewer of those researches have tackled the consideration of uncertainties in TCTP. Zheng and Kumaraswamy (2005), Leu andYang (1998), Moselhi andRoofigari (2013), Moselhi and Alshibani (2013), and Kalhor et al (2011) proposed a fuzzy method for a stochastic TCT problem. Fuzzy set theory dominated those researches due to its capacity to produce the results in fewer runs.…”

Optimized resource-constrained method for project schedule compression

“…On the contrary, clients tend to enforce accelerated project delivery to cope with current market conditions and meet stakeholder demands. The process of accelerating the completion of construction projects is referred to in the literature as the time-cost trade-off where a delicate balance between the overall cost of a project and its duration is established to achieve the desired overall project objectives (Moselhi and Esfahan, 2013). The schedule duration reduction results in a higher direct cost and a lower indirect cost.…”