Beyond the Edge of Feasibility: Analysis of Bottlenecks

Bonyadi, Mohammad Reza, Michalewicz, Zbigniew and Wagner, Markus (2014). Beyond the Edge of Feasibility: Analysis of Bottlenecks. In: Simulated Evolution and Learning (Seal 2014): Proceedings of the 10th International Conference on Simulated Evolution and Learning. 10th International Conference on Simulated Evolution and Learning (SEAL), Dunedin, New Zealand, (431-442). 15-18 December 2014. doi:10.1007/978-3-319-13563-2_37


Author Bonyadi, Mohammad Reza
Michalewicz, Zbigniew
Wagner, Markus
Title of paper Beyond the Edge of Feasibility: Analysis of Bottlenecks
Conference name 10th International Conference on Simulated Evolution and Learning (SEAL)
Conference location Dunedin, New Zealand
Conference dates 15-18 December 2014
Proceedings title Simulated Evolution and Learning (Seal 2014): Proceedings of the 10th International Conference on Simulated Evolution and Learning   Check publisher's open access policy
Place of Publication New York, NY, United States
Publisher Springer
Publication Year 2014
Year available 2014
Sub-type Fully published paper
DOI 10.1007/978-3-319-13563-2_37
Open Access Status Not yet assessed
ISBN 9783319135625
ISSN 0302-9743
Volume 8886
Start page 431
End page 442
Total pages 12
Language eng
Abstract/Summary The productivity of real-world systems is often limited by so-called bottlenecks. Hence, usually companies are not only interested in finding the best ways to schedule their current resources so that their benefits are maximized optimization, but, in order to increase the productivity, they also conduct some analysis to find bottlenecks in their system and eliminate them in the most efficient way e.g., with the lowest investment. We show that the current frequently used analysis based on average shadow price for identifying bottlenecks has some limitations: 1 it is limited to linear constraints, 2 it does not consider all potential sources for bottlenecks in a system, and 3 it does not provide adequate tools for decision makers to find the best way of investment to eliminate bottlenecks and maximize the profit they can gain. We propose a more comprehensive definition of bottlenecks that covers these limitations. Based on this new definition, we propose a multi-objective model for the benefit and investment. The solution for this model provides the best way of investment in resources to achieve maximum profit. As the proposed model is multi-objective and non-linear, it opens an important opportunity for the application of evolutionary algorithms, which can subsequently have a significant impact on the decision making process of companies.
Keyword Constraints
Bottlenecks
What-if analysis
Feasibility
Shadow Price
Constraints
Decision
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Conference Paper
Sub-type: Simulated Evolution and Learning (Seal 2014)
Collection: Centre for Advanced Imaging Publications
 
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