A hybrid model based on Siemens and data envelopment analysis to solve the time-cost trade-off problem considering multi factors

Document Type : Research Paper

Authors

1 Department of industrial management, South Tehran Branch, Islamic Azad University, Tehran, Iran

2 Department of Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran

3 Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

Abstract

One of the most common problems in the context of project management is the project delay issue. Delay in projects has been caused by many factors, and most of them can be controlled by proper management. One of the most important measures which reflect projects success is its scheduling performance. The capabilities and limitations of an organization for advancing projects are under continuous changes and transformations. Meanwhile, environmental and technological changes over time provide the basis for changes in organizational strategy. Today, the world is moving toward planning and execution of projects by considering factors such as time and cost from the beginning, and these factors are considered simultaneously. In the management of any project, cost, time, risk and quality are critical and essential factors. All of these factors should be in their best condition, so the project can be handled in the best possible way. This paper is looking for a method that includes quality, risk and cost measures in the time-cost tradeoff problem. The "resources" aspect is effective for each of these factors. These resources consist of human resources, machines and financial resources. There are various methods for establishing a tradeoff between time and cost. In this article, a heuristic algorithm based on data envelopment analysis had been developed for multi-criteria time-cost tradeoff. The results of applying this heuristic method to a numerical case study have been reported.

Keywords

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Volume 14, Issue 1
January 2023
Pages 2687-2699
  • Receive Date: 17 October 2022
  • Revise Date: 27 December 2022
  • Accept Date: 03 January 2023