Integrated Fuzzy-HMH for project uncertainties in time-cost tradeoff problem

Time-cost tradeoff (TCT) problem in project scheduling studies how to schedule project activities to achieve a tradeoff between project cost and project completion time. It gives project planners both challenges and opportunities to work out the best plan that optimizes time and cost to complete a project. In this paper, we present a novel method which examines the effects of project uncertainties on both, the duration as well as the cost of the activities. This method integrates a fuzzy logic framework with Hybrid Meta-Heuristic. Hybrid Meta-Heuristic (HMH) is an innovative approach which hybridizes a multiobjective genetic algorithm and simulated annealing. Integration of HMH and fuzzy logic is referred to as 'integrated Fuzzy-HMH'. A rule based fuzzy logic framework brings up changes in the duration and the cost of each activity for the input uncertainties and HMH searches for Pareto-optimal front (TCT profile) for a given set of time-cost pair of each project activity. Two standard test problems from the literature are attempted using HMH. A case study of TCT problem is solved using integrated Fuzzy-HMH. The method solves time-cost tradeoff problems within an uncertain environment and carries out its sensitivity analysis.