A new resource buffer insertion approach for proactive resource investment problem. (August 2020)

• Record Type: Journal Article
• Authors: Shariatmadari, Mohammad; Nahavandi, Nasim
• Is Part Of: Computers & industrial engineering. Volume 146(2020)
• Publication Date: 2020-08
• Subjects: Resource Investment Problem (RIP) -- Resource-Constrained Project Scheduling Problem (RCPSP) -- Surrogate measures -- Proactive scheduling -- Resource buffer -- Robustness enhancement; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106582
• Languages: English
• ISSNs: 0360-8352

Abstract

Graphical abstract: The relationship between mean Δ P M α P M St I and investment limit (α). Highlights: This paper investigates robustness enhancement of an existing schedule. Twenty surrogate measures are suggested. The performance of surrogate measures are evaluated by test problems. An iterative robustness enhancement algorithm is proposed. An estimation method is proposed for determining the required investment. Abstract: The majority of research has concentrated on the creation of robust schedules to manage the uncertainties and disruptions that called pro-active scheduling. Different from previous research on pro-active scheduling, this paper investigates robustness enhancement of an existing schedule using inserting resource buffers instead of creating robust schedule. The present study aims to present an algorithm for robustness enhancement of schedules through resource buffer insertion during the planning horizon in which the availability of resources varies with time and the uncertainty is in the required renewable resources for activities. Since surrogate measures can be used to measure schedule robustness, 20 resources and resource/time-oriented surrogate measures are proposed and then, using computational results, their performance is evaluated. The results show that resource/time-oriented measures have relatively better performance than other measures. Finally, an iterative algorithm for robustness enhancement based on using the best surrogate measure is proposed and required investment is estimated. According to the estimation process, it will be shown that the slope of robustness enhancement rate towards the robustness investment is always descending.