An evolutionary optimization method to determine optimum degree of activity accelerating and overlapping in schedule compression

Abstract

Compressing project schedule using activity accelerating and overlapping requires that an intensive time–cost trade-off analysis be carried out, to determine costs and benefits for each day of compression. However, the cost elements and implications of compression techniques differ significantly, since activity accelerating imposes extra direct cost whereas activity overlapping adds a risk of changes and rework. Such a trade-off becomes even more complicated in capital projects comprised of a large number of schedule activities and relationships. The variety of combinations of accelerating and overlapping of different activities in these complex networks can offer numerous possibilities for compression with various costs and potential risks. The lack of a reliable analytical tool for performing a precise cost-benefit analysis causes this critical task to be performed in a subjective manner during the planning stage of projects. The purpose of this paper is to present an advanced method using a multi-objective evolutionary optimization tool seeking the optimum degree of accelerating and overlapping during the schedule compression process. This optimization technique would be beneficial in maximizing project benefits while meeting the intended target dates.