A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study

2020 ◽  
Author(s):  
Ghazaleh Ahmadi ◽  
Reza Tavakkoli-Moghaddam ◽  
Armand Baboli ◽  
Mehdi Najafi
Keyword(s):  
Decision Support ◽  
Search And Rescue ◽  
Decision Support Model ◽  
Support Model

Widely Applicable Multi-Variate Decision Support Model for Market Trend Analysis and Prediction with Case Study in Retail

2014 ◽  
pp. 989-1018 ◽  
Author(s):  
Leo Mršić
Keyword(s):  
Time Series ◽  
Decision Support ◽  
Bayesian Network ◽  
Real Life ◽  
Heterogeneous Data Source ◽  
Decision Support Model ◽  
Market Trends ◽  
Series Transformation ◽  
Support Model

Chapter explains efficient ways of dealing with business problems of analyzing market environment and market trends under complex circumstances using heterogeneous data source. Under the assumption that used data can be expressed as time series, widely applicable multi variate model is explained together with case study in textile retail. This Chapter includes an overview of research conducted with a brief explanation of approaches and models available today. A widely applicable multi-variate decision support model is presented with advantages, limitations, and several variations for development. The explanation is based on textile retail case study with model wide range of possible applications in perspective. Complex business environment issues are simulated with explanation of several important global trends in textile retail in past seasons. Non-traditional approaches are revised as tools for a better understanding of modern market trends as well as references in relevant literature. A widely applicable multi-variate decision support model and its usage is presented through built stages and simulated. Model concept is based on specific time series transformation method in combination with Bayesian logic and Bayesian network as final business logic layer with front end interface built with open source Bayesian network tool. Explained case study provides one of the most challenging issue in textile retail: market trends seasonal/weather dependence. Separate outcomes for different scenario analysis approaches are presented on real life data from a textile retail chain located in Zagreb, Croatia. Chapter ends with a discussion about similar research’s, wide applicability of presented model with references for future research.

scholarly journals A Zero-Waste Multi-Criteria Decision-Support Model for the Iron and Steel Industry in Developing Countries: A Case Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2832
Author(s):  
Yolandi Schoeman ◽  
Paul Oberholster ◽  
Vernon Somerset
Keyword(s):  
Decision Support ◽  
Waste Management ◽  
Steel Industry ◽  
Industrial Waste ◽  
Iron And Steel Industry ◽  
Decision Support Model ◽  
Iron And Steel ◽  
Zero Waste ◽  
Support Model

The iron and steel industry is a major global industry that consumes vast quantities of energy and causes environmental degradation through greenhouse gas emissions and industrial waste generation, treatment, and disposal. There is a need to manage complex iron and steel industrial waste in Africa, which requires a system engineering approach to zero waste management as informed by multi-criteria decision-making. The purpose of the current study was to develop a hybrid four-step multi-criteria decision-support model, the i-ZEWATA (Industrial Zero Waste Tiered Analysis). I-ZEWATA acts as a road map to understand, design, assess, and evaluate the iron and steel industrial waste systems with the ultimate objective of moving towards and achieving a zero-waste footprint. The results demonstrate that iron and steel waste can be identified, visualized, prioritized, and managed to promote zero-waste by applying a system-engineered approach. Additionally, relationship patterns to environmental, social, operational, and economic aspects with system behavioral patterns and outcomes were identified. It was clear from the case study in South Africa that, although technology and solution investment is essential, waste management, valorization, and treatment components require a concerted effort to improve industrial waste operational management through effective zero-waste decision-support towards a circular economy.

A decision support model for traffic congestion in protected areas: A case study of Shiretoko National Park

2013 ◽  
Vol 8 ◽  
pp. 18-27 ◽  
Author(s):  
Kensuke Ishikawa ◽  
Naoko Hachiya ◽  
Tetsuya Aikoh ◽  
Yasushi Shoji ◽  
Katsuhiro Nishinari ◽  
...  
Keyword(s):  
Decision Support ◽  
Protected Areas ◽  
Traffic Congestion ◽  
National Park ◽  
Decision Support Model ◽  
Support Model

A GIS-based multi-criteria decision support model for planning municipal solid waste collection points: A case study of Çağdaş Neighbourhood, Çiğli District, Izmir, Turkey

2021 ◽  
pp. 0734242X2110637
Author(s):  
Sedat Yalcinkaya ◽  
Sevin Uzer
Keyword(s):  
Decision Support ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Pollutant Emissions ◽  
Walking Distance ◽  
Waste Collection ◽  
Collection System ◽  
Decision Support Model ◽  
Support Model

This study aims to develop a geographic information system (GIS)-based multi-criteria decision support model to create optimal plans for locating municipal solid waste (MSW) collection points. The model performs a series of consecutive GIS-based spatial analyses to determine alternative plans. Then, it weighs the alternatives considering the social, economic and environmental criteria to determine the optimum solution through analytical hierarchy process. The model was implemented as a case study in Çağdaş neighbourhood of Izmir, Turkey. A total of 42 locations were determined as the optimum collection points out of 245 possible collection points, which yields 39% reduction in collection points compared to the existing system. Total number of waste bins and average walking distance to waste collection points were calculated as 129 and 33 m, respectively. The municipal authority would spend 48.79 $ day−1 on fuel for waste collection and transport. In addition, daily air pollutant emissions generated during the operations were estimated as 2.052 g CO, 0.231 g NMVOC, 8.409 g NOx, 0.954 g N2O, 0.260 g NH3, 0.000227 g Pb and 0.0231 g PM 2.5. The results indicated that 14 out of 69 collection points in the existing collection system were not allocated to any waste source geographically. This study presents a unique method for planning MSW collection points on two key aspects: (1) development of a novel method to determine all possible collection point locations using Thiessen polygons and (2) presenting a holistic planning method considering the impacts of the collection system on the waste generators and waste collectors.

scholarly journals Development of an Agricultural Primary Productivity Decision Support Model: A Case Study in France

2019 ◽  
Vol 7 ◽  
Author(s):  
Taru Sandén ◽  
Aneta Trajanov ◽  
Heide Spiegel ◽  
Vladimir Kuzmanovski ◽  
Nicolas P. A. Saby ◽  
...  
Keyword(s):  
Decision Support ◽  
Primary Productivity ◽  
Decision Support Model ◽  
Support Model
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