Optimum Solution of Resource Leveling Problem by Evaluating the Whole Search Domain

Abstract

The endeavor to minimize the fluctuations of the resource assignments without postponing the project deadline is named as resource leveling problem. This problem is solved by heuristic methods, consist of simple rules, meta-heuristic methods, explore the search domain systematically but randomly, and analytical methods. Nevertheless, aforementioned approaches come to be insufficient when the number of activity of the project increases which oversize the search domain of the resource leveling problem. In this study, the number of the feasible solutions is determined by detecting the number of feasible schedules obtained by delaying the noncritical activities without violating the restrictions on the activities. The entire search domain is evaluated and the optimum feasible solution is obtained in a guaranteed manner. Suitability of the resource distribution is evaluated by minimum moment metric. A spreadsheet application is developed and macro is written by Visual Basic programming language to implement the developed method. In the literature survey, twenty seven resource leveling problems are collected and optimum solutions of them are obtained by the developed method. Definition of the parameters and the evaluation of the search domain of the resource leveling problem by the spreadsheet application are explained in detail on two of the solved case study problems so that the researchers can implement the developed method. Moreover the developed method is coded on C++ in order to expedite the computations. Test problems are also solved by genetic algorithm and the computation duration and the obtained results are compared with the proposed method. The comparison reveals that the developed method can be implemented for optimizing the resource distribution. Moreover, this research contributes to the literature by providing a methodology for the determination of the search domain of the resource leveling problem.