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, 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.
Highlights
Completing the project within time and cost limits are two important objectives of project management
The paper shows that a simple approach based on simple heuristic and deterministic simulation can give good result comparable to sophisticated optimization techniques
Several sophisticated optimization and soft-computing techniques such as Dynamic Programming, Integer Programming, Genetic Algorithm, Ant Colony Optimization etc. that have been used for finding efficient solution to activity modes selection problem
Summary
Completing the project within time and cost limits are two important objectives of project management. The proposed method uses limited search to arrive at an efficient solution In many problems, such as the activity modes selection problem, the assignable parameters (input) that affect the result (output) are not fully known. The selection of activity for execution in expedited mode is determined based on assignable parameters having weight “w” and a random number having weight (1 – w). Due to inclusion of random component the overall activity index for expediting varies within a given range around the index determined from assignable parameters We refer this range as search space. When no weight is given to assignable parameter (w = 0), the search space is same as the total space It will require very large number of trials to find an efficient solution. The method was applied to select the activity mode of activities to reduce the duration of project network from 35 time units to 30 time units
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