Activity modes selection for project crashing through deterministic simulation

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Abstract

Purpose: The time-cost trade-off problem addressed by CPM-based analytical approaches, assume unlimited resources and the existence of a continuous time-cost function. However, given the discrete nature of most resources, the activities can often be crashed only stepwise. Activity crashing for discrete time-cost function is also known as the activity modes selection problem in the project management. This problem is known to be NP-hard. Sophisticated optimization techniques such as Dynamic Programming, Integer Programming, Genetic Algorithm and Ant Colony Optimization have been used for finding efficient solution to activity modes selection problem. The paper presents a simple method that can provide efficient solution to activity modes selection problem for project crashing. Design/methodology/approach: Simulation based method implemented on electronic spreadsheet to determine activity modes for project crashing. The method is illustrated with the help of an example. Findings: The paper shows that a simple approach based on simple heuristic and deterministic simulation can give good result comparable to sophisticated optimization techniques. Research limitations/implications: The simulation based crashing method presented in this paper is developed to return satisfactory solutions but not necessarily an optimal solution. Practical implications: The use of spreadsheets for solving the Management Science and Operations Research problems make the techniques more accessible to practitioners. Spreadsheets provide a natural interface for model building, are easy to use in terms of inputs, solutions and report generation, and allow users to perform what-if analysis. Originality/value: The paper presents the application of simulation implemented on a spreadsheet to determine efficient solution to discrete time cost tradeoff problem.

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APA

Mohanty, A., Mishra, J., & Satpathy, B. (2011). Activity modes selection for project crashing through deterministic simulation. Journal of Industrial Engineering and Management, 4(4), 610–623. https://doi.org/10.3926/jiem.224

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