{"title":"Integrating Topological and Hydraulic Attributes for Robustness Analysis of Water Distribution Networks","authors":"Seyed Ashkan Zarghami, I. Gunawan, F. Schultmann","doi":"10.46254/J.IEOM.20190101","DOIUrl":"https://doi.org/10.46254/J.IEOM.20190101","url":null,"abstract":"Researchers are recognizing that the robustness evaluation of Water Distribution Networks (WDNs) is of great importance for reducing the impact of disruptive events. Yet, very few methods to measure the robustness of WDNs have been developed. These methods mainly focus on either the topological features or the hydraulic attributes of WDNs and fail to provide a comprehensive picture of the robustness characteristics of WDNs. The work described herein proposes a new robustness index to measure the heterogeneity of WDNs drawing on informational entropy theory. The paper attempts to shift away from an exclusive topological viewpoint or a pure hydraulic approach, towards a combined topological and hydraulic analysis. The main emphasis is on the influence of an individual node on the overall network performance. The use of the proposed index is illustrated with a real-world WDN of an Australian town. The results highlight the significance of integrating the topological and hydraulic metrics for a reliable assessment of robustness in WDNs.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128757888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"New Framework to Optimize Leagile Supply Chain Design","authors":"D. Nguyen, T. Dao","doi":"10.46254/j.ieom.20190104","DOIUrl":"https://doi.org/10.46254/j.ieom.20190104","url":null,"abstract":"The literature of Leagile supply chain (LASC) is lacking of the concurrence between supply chain (SC) design and product design, and missing the placement of decoupling point (DP) in the SC design. Therefore, the paper aims at presenting a novel framework to optimise LASC design while fulfilling the aforementioned gaps. The first step utilises Lean tools to identify the optimal architecture of product families through the so-called Leagile bill-of-material in product design. This phrase intends to reduce the storage keeping unit of components (leaner) while increasing their combining ability in a wider range of new products (more agile). Meanwhile, the second stage outlines the preliminary configuration of the future supply chain and transforms it into the Lean system. Next, the supplier network of this chain is matched with the product structure. The last step formulates the issue in one mathematical model to define the optimal LASC’s configuration, which includes positioning the best DP in various delivery lead time. In discussing the obtained solutions, the article complements to the theoretical basis by examining the locations of DP corresponding to the product’s complexity. The whole framework is illustrated by one specific example and solved by Priority Generic Algorithm Meta-Heuristic, programed with MATLAB.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128076095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bankruptcy prediction for Japanese corporations using support vector machine, artificial neural network, and multivariate discriminant analysis","authors":"Matsumaru Masanobu, Kaneko Shoichi, Katagiri Hideki, Kawanaka Takaaki","doi":"10.46254/j.ieom.20190106","DOIUrl":"https://doi.org/10.46254/j.ieom.20190106","url":null,"abstract":"This study predicted the bankruptcy risk of companies listed in Japanese stock markets for the entire industry and individual industries using multiple discriminant analysis (MDA), artificial neural network (ANN), and support vector machine (SVM) and compared the methods to determine the best one. The financial statements of the companies listed in the Tokyo Stock Exchange in Japan were used as data. The data of 244 companies that went bankrupt between 1991 and 2015 were used. Additionally, the data of 64,708 companies that did not go bankrupt between 1991 and 2015 (24 years) were used. The data was acquired from the Nikkei NEEDS database. It was found from the results of empirical analysis that the SVM is more accurate than the other models in predicting the bankruptcy risk of companies. In the ANN analysis and MDA, bankruptcy prediction could be made accurately only for some individual industries. In contrast, the SVM could predict the bankruptcy risk of companies almost perfectly for either entire and individual industries. This bankruptcy prediction model can help customers, investors, and financiers prevent losses by focusing on the financial indicators before finalizing transactions.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130630157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real Options Framework for Dealing with Uncertainty in Project Management: A Moroccan Infrastructure Project","authors":"Jihane Gharib, A. Berrado, L. Benabbou","doi":"10.46254/j.ieom.20190105","DOIUrl":"https://doi.org/10.46254/j.ieom.20190105","url":null,"abstract":"The Real Options Valuation allows for the consideration of possible options that are instinctively embedded in investment projects, in which the decision-makers have the flexibility to respond to the outcome of uncertainty. The business managers’ abilities to react to future market conditions tend to impact the value of the investment project by maintaining or improving the upside potential and limiting the downside loss. This process must be regulated by a decision analysis model, capable of capturing the particularities of each project.\u0000This paper presents detailed literature review of the real options, includes their area of applications in the literature, then proposes a framework to ease the understanding and the use of this method. Later, a case study of a Moroccan infrastructure project, that had already undergone an evaluation, is outlaid. The paper fully addresses the gaps of the previous study, provides a corrected model for an improved valuation of this project and a suitable use of real options. It also illustrates its application and analyzes the obtained results.","PeriodicalId":268888,"journal":{"name":"International Journal of Industrial Engineering and Operations Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133515622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}