Multi-criteria analysis applied to multi-objective optimal pump scheduling in water systems

This work presents a multi-criteria-based approach to automatically select specific non-dominated solutions from a Pareto front previously obtained using multi-objective optimization to find optimal solutions for pump control in a water supply system. Optimal operation of pumps in these utilities is paramount to enable water companies to achieve energy efficiency in their systems. The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the Pareto solutions found by the Non-Dominated Sorting Genetic Algorithm (NSGA-II) employed to solve the multi-objective problem. Various scenarios are evaluated under leakage uncertainty conditions, resulting in fuzzy solutions for the Pareto front. This paper shows the suitability of the approach for quasi real-world problems. In our case-study, the obtained solutions for scenarios including leakage represent the best trade-off among the optimal solutions, under some considered criteria, namely, operational cost, operational lack of service, pressure uniformity and network resilience. Potential future developments could include the use of clustering alternatives to evaluate the goodness of each solution under the considered evaluation criteria

A hybrid performance evaluation system for notebook computer ODM companies

[[abstract]]The aim of the paper is to fulfill this need by building a conceptual framework for measuring the business performance of notebook computer ODM (Original Design Manufacturer) companies carried out to investigate how performance is understood and to identify the potential dimensions to improvement. In the process, a multiple criteria procedure is used to assess the performance in these companies. We explore the performance-evaluation systems by using fuzzy AHP and VIKOR techniques. The evidence from the investigation showed that supply chain capability and manufacturing capability are the top two indicators for the notebook computer ODM companies’ performance. Furthermore, it was found that Quanta and Compal have the relative high business performance among these companies. The research provides evidence which establishes whether benchmarking provides a real and lasting benefit to notebook computer ODM companies. A series of managerial implications are set forth and discussed.[[journaltype]]國外[[incitationindex]]SSCI[[booktype]]紙本[[countrycodes]]NG

More Important Than Their Money Offering: The Application of Action Research, ANP and TOPSIS to Real Estate Investing

This thesis examines the supplier selection process of non-institutional financial capital suppliers by small-scale real estate investing organizations and focuses specifically on the key criterion that real estate investing companies should seek when selecting and evaluating potential suppliers to promote an ideal partnership. These partnerships can provide the real estate investing organizations with vital capital access that allows business growth, larger transaction sizes, and greater volume but can be detrimental if the partners are ill-matched. Without a reputation or industry experience, many novice real estate investors are unaware of what qualities are most important to pursue when forming these critical relationships and simply accept any partner willing to provide capital. By using Action Research and quantitative methodologies of Analytical Network Process (ANP) and TOPSIS, this thesis documents the development of a start-up, solo-entrepreneurial investing organization and the actionable creation of an organizational supplier onboarding tool. The study surveys nineteen real estate industry expert participants and ultimately highlights six criterions as most important when selecting and evaluating potential financial capital suppliers: trustworthiness, motivation, quality of past experience, collateral and capacity, risk tolerance and risk appetite, and responsiveness. Using these findings, the entrepreneurial organization successfully develops and launches a free, online personalized questionnaire service for the benefit of both the future potential financial suppliers and the investing organization that strengthens partner communication, clarifies organizational culture and business development, and promotes overall service supply chain growth

Multiple criteria decision making in application layer networks

This work is concerned with the conduct of MCDM by intelligent agents trading commodities in ALNs. These agents consider trustworthiness in their course of negotiation and select offers with respect to product price and seller reputation. --Grid Computing

Developing a diagnostic heuristic for integrated sugarcane supply and processing systems.

Doctoral Degrees. University of KwaZulu-Natal, Pietermaritzburg.Innovation is a valuable asset that gives supply chains a competitive edge. Moreover, the adoption of innovative research recommendations in agricultural value chains and integrated sugarcane supply and processing systems (ISSPS) in particular has been relatively slow when compared with other industries such as electronics and automotive. The slow adoption is attributed to the complex, multidimensional nature of ISSPS and the perceived lack of a holistic approach when dealing with certain issues. Most of the interventions into ISSPS often view the system as characterised by tame problems hence, the widespread application of traditional operations research approaches. Integrated sugarcane supply and processing systems are, nonetheless, also characterised by wicked problems. Interventions into such contexts should therefore, embrace tame and/or wicked issues. Systemic approaches are important and have in the past identified several system-scale opportunities within ISSPS. Such interventions are multidisciplinary and employ a range of methodologies spanning across paradigms. The large number of methodologies available, however, makes choosing the right method or a combination thereof difficult. In this context, a novel overarching diagnostic heuristic for ISSPS was developed in this research. The heuristic will be used todiagnose relatively small, but pertinent ISSPS constraints and opportunities. The heuristic includes a causal model that determines and ranks linkages between the many domains that govern integrated agricultural supply and processing systems (IASPS) viz. biophysical, collaboration, culture, economics, environment, future strategy, information sharing, political forces, and structures. Furthermore, a diagnostic toolkit based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was developed. The toolkit comprises a diagnostic criteria and a suite of systemic tools. The toolkit, in addition, determines thesuitability of each tool to diagnose any of the IASPS domains. Overall, the diagnostic criteria include accessibility, interactiveness, transparency, iterativeness, feedback, cause-and-effect logic, and time delays. The tools considered for the toolkit were current reality trees, fuzzy cognitive maps (FCMs), network analysis approaches, rich pictures (RP), stock and flow diagrams, cause and effect diagrams (CEDs), and causal loop diagrams (CLDs). Results from the causal model indicate that collaboration, structure and information sharing had a high direct leverage over the other domains as these were associated with a larger number of linkages. Collaboration and structure further provided dynamic leverage as these were also part of feedback loops. Political forces and the culture domain in contrast, provided lowleverage as these domains were only directly linked to collaboration. It was further revealed that each tool provides a different facet to complexity hence, the need for methodological pluralism. All the tools except RP could be applied, to a certain extent, across both appreciation and analysis criteria. Rich pictures do not have causal analysis capabilities viz. cause-and-effect logic, time delays and feedback. Stock and flow diagrams and CLDs conversely, met all criteria. All the diagnostic tools in the toolkit could be used across all the system domains except for FCMs. Fuzzy cognitive maps are explicitly subjective and their contribution lies outside the objective world. Caution should therefore be practiced when FCMs areapplied within the biophysical domain. The heuristic is only an aid to decision making. The decision to select a tool or a combination thereof remains with the user(s). Even though the heuristic was demonstrated at Mhlume sugarcane milling area, it is recommended that other areas be considered for future research. The heuristic itself should continuously be updated with criteria, tools and other domain dimensions

Multi-criteria analysis applied to multi-objective optimal pump scheduling in water systems

[EN] This work presents a multi-criteria-based approach to automatically select specific non-dominated solutions from a Pareto front previously obtained using multi-objective optimization to find optimal solutions for pump control in a water supply system. Optimal operation of pumps in these utilities is paramount to enable water companies to achieve energy efficiency in their systems. The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the Pareto solutions found by the non-dominated sorting genetic algorithm (NSGA-II) employed to solve the multi-objective problem. Various scenarios are evaluated under leakage uncertainty conditions, resulting in fuzzy solutions for the Pareto front. This paper shows the suitability of the approach for quasi real-world problems. In our case-study, the obtained solutions for scenarios including leakage represent the best trade-off among the optimal solutions, under some considered criteria, namely, operational cost, operational lack of service, pressure uniformity and network resilience. Potential future developments could include the use of clustering alternatives to evaluate the goodness of each solution under the considered evaluation criteria.Carpitella, S.; Brentan, BM.; Montalvo Arango, I.; Izquierdo Sebastián, J.; Certa, A. (2019). Multi-criteria analysis applied to multi-objective optimal pump scheduling in water systems. Water Science & Technology: Water Supply. 19(8):2338-2346. https://doi.org/10.2166/ws.2019.115S23382346198Ancău, M., & Caizar, C. (2010). The computation of Pareto-optimal set in multicriterial optimization of rapid prototyping processes. Computers & Industrial Engineering, 58(4), 696-708. doi:10.1016/j.cie.2010.01.015Aşchilean, I., Badea, G., Giurca, I., Naghiu, G. S., & Iloaie, F. G. (2017). Choosing the Optimal Technology to Rehabilitate the Pipes in Water Distribution Systems Using the AHP Method. Energy Procedia, 112, 19-26. doi:10.1016/j.egypro.2017.03.1109Brentan, B., Meirelles, G., Luvizotto, E., & Izquierdo, J. (2018). Joint Operation of Pressure-Reducing Valves and Pumps for Improving the Efficiency of Water Distribution Systems. Journal of Water Resources Planning and Management, 144(9), 04018055. doi:10.1061/(asce)wr.1943-5452.0000974Certa, A., Enea, M., Galante, G. M., & La Fata, C. M. (2017). ELECTRE TRI-based approach to the failure modes classification on the basis of risk parameters: An alternative to the risk priority number. Computers & Industrial Engineering, 108, 100-110. doi:10.1016/j.cie.2017.04.018Chen, C.-T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1-9. doi:10.1016/s0165-0114(97)00377-1Cruz-Reyes, L., Fernandez, E., Sanchez, P., Coello Coello, C. A., & Gomez, C. (2017). Incorporation of implicit decision-maker preferences in multi-objective evolutionary optimization using a multi-criteria classification method. Applied Soft Computing, 50, 48-57. doi:10.1016/j.asoc.2016.10.037Farmani, R., Ingeduld, P., Savic, D., Walters, G., Svitak, Z., & Berka, J. (2007). Real-time modelling of a major water supply system. Proceedings of the Institution of Civil Engineers - Water Management, 160(2), 103-108. doi:10.1680/wama.2007.160.2.103Hadas, Y., & Nahum, O. E. (2016). Urban bus network of priority lanes: A combined multi-objective, multi-criteria and group decision-making approach. Transport Policy, 52, 186-196. doi:10.1016/j.tranpol.2016.08.006Hamdan, S., & Cheaitou, A. (2017). Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach. Computers & Operations Research, 81, 282-304. doi:10.1016/j.cor.2016.11.005Ho, W. (2008). Integrated analytic hierarchy process and its applications – A literature review. European Journal of Operational Research, 186(1), 211-228. doi:10.1016/j.ejor.2007.01.004Jowitt, P. W., & Germanopoulos, G. (1992). Optimal Pump Scheduling in Water‐Supply Networks. Journal of Water Resources Planning and Management, 118(4), 406-422. doi:10.1061/(asce)0733-9496(1992)118:4(406)Jowitt, P. W., & Xu, C. (1990). Optimal Valve Control in Water‐Distribution Networks. Journal of Water Resources Planning and Management, 116(4), 455-472. doi:10.1061/(asce)0733-9496(1990)116:4(455)Kurek, W., & Ostfeld, A. (2013). Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems. Journal of Environmental Management, 115, 189-197. doi:10.1016/j.jenvman.2012.11.030Lima, G. M., Luvizotto, E., & Brentan, B. M. (2017). Selection and location of Pumps as Turbines substituting pressure reducing valves. Renewable Energy, 109, 392-405. doi:10.1016/j.renene.2017.03.056Mala-Jetmarova, H., Sultanova, N., & Savic, D. (2017). Lost in optimisation of water distribution systems? A literature review of system operation. Environmental Modelling & Software, 93, 209-254. doi:10.1016/j.envsoft.2017.02.009Montalvo, I., Izquierdo, J., Pérez-García, R., & Herrera, M. (2014). Water Distribution System Computer-Aided Design by Agent Swarm Optimization. Computer-Aided Civil and Infrastructure Engineering, 29(6), 433-448. doi:10.1111/mice.12062Odan, F. K., Ribeiro Reis, L. F., & Kapelan, Z. (2015). Real-Time Multiobjective Optimization of Operation of Water Supply Systems. Journal of Water Resources Planning and Management, 141(9), 04015011. doi:10.1061/(asce)wr.1943-5452.0000515Ostfeld, A., Uber, J. G., Salomons, E., Berry, J. W., Hart, W. E., Phillips, C. A., … Walski, T. (2008). The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms. Journal of Water Resources Planning and Management, 134(6), 556-568. doi:10.1061/(asce)0733-9496(2008)134:6(556)Todini, E. (2000). Looped water distribution networks design using a resilience index based heuristic approach. Urban Water, 2(2), 115-122. doi:10.1016/s1462-0758(00)00049-2Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of Biomedical Informatics, 53, 390-404. doi:10.1016/j.jbi.2014.11.012Żak, J., & Kruszyński, M. (2015). Application of AHP and ELECTRE III/IV Methods to Multiple Level, Multiple Criteria Evaluation of Urban Transportation Projects. Transportation Research Procedia, 10, 820-830. doi:10.1016/j.trpro.2015.09.03

Implementing Multi Agent Systems (MAS)-based trust and reputation in smart IoT environments : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University

The Internet of Things (IoT) provides advanced services by interconnecting a huge number of heterogeneous smart things (virtual or physical devices) through existing interoperable information and communication technologies. As IoT devices become more intelligent, they will have the ability to communicate and cooperate with each other. In doing so, enormous amount of sensitive data will flow within the network such as a credit card information, medical data, factory details, pictures and videos. With sensitive data flowing through the network, privacy becomes one of most important issues facing IoT. Studies of data sensitivity and privacy indicate the importance of evaluating the trustworthiness of IoT participants to maximize the satisfaction and the performance of the IoT applications. It is also important to maintain successful collaboration between the devices deployed in the network and ensure all devices operate in a trustworthy manner. This research aims to determine: How to select the best service provider in an IoT environment based on the trustworthiness and the reputation of the service provider? To achieve this, we proposed an IoT agent-based decentralized trust and reputation model IoT-CADM (Comprehensive Agent-based Decision-making Model for IoT) to select the best service providers for a particular service based on multi-context quality of services. IoT-CADM as a novel trust and reputation model, is developed for the smart multi-agent IoT environment to gather information from entities and score them using a new trust and reputation scoring mechanism. IoT-CADM aims to ensure that the service consumers are serviced by the best service providers in the IoT environment which in turn maximizes the service consumers’ satisfaction, which lead the IoT entities to operate and make-decisions on behalf of its owner in a trustworthy manner. To evaluate the performance of the proposed model against some other well-known models like ReGreT, SIoT, and R-D-C, we implemented a scenario based on the SIPOC Supply Chain approach developed using an agent development framework called JADE. This research used the TOPSIS approach to compare and rank the performance of these models based on different parameters that have been chosen carefully for fair comparison. The TOPSIS result confirmed that the proposed IoT-CADM has the highest performance. In addition, the model can be tuned to its parameters weight to adapt to varying scenarios in honest and dishonest agents’ environments

Efficiency measurement of cloud service providers using network data envelopment analysis

An increasing number of organizations and businesses around the world use cloud computing services to improve their performance in the competitive marketplace. However, one of the biggest challenges in using cloud computing services is performance measurement and the selection of the best cloud service providers (CSPs) based on quality of service (QoS) requirements (Duan, 2017). To address this shortcoming in this article we propose a network data envelopment analysis (DEA) method in measuring the efficiency of CSPs. When network dimensions are taken into consideration, a more comprehensive analysis is enabled where divisional efficiency is reflected in overall efficiency estimates. This helps managers and decision makers in organizations to make accurate decisions in selecting cloud services. In the current study, variable returns to scale (VRS), the non-oriented network slacks-based measure (SBM) model and input-oriented and output-oriented SBM models are applied to measure the performance of 18 CSPs. The obtained results show the superiority of the network DEA model and they also demonstrate that the proposed model can evaluate and rank CSPs much better than compared to traditional DEA models

A framework for QoS driven user-side cloud service management

This thesis presents a comprehensive framework that assists the cloud service user in making cloud service management decisions, such as service selection and migration. The proposed framework utilizes the QoS history of the available services for QoS forecasting and multi-criteria decision making. It then integrates all the inherent necessary processes, such as QoS monitoring, forecasting, service comparison and ranking to recommend the best and optimal decision to the user

Automatic Maritime Traffic Anomalous Behaviors Detection

Maritime traffic plays a very important role in the world economy, with over 90% of global trading done through naval transportation. The high amount of vessel traffic, mainly due to cargo transportation, leads to several new risks, threats, and concerns, such as increased criminal activity in the sea. The OVERSEE project is proprietary software developed by Crit ical Software and used by Marinha Portuguesa, Irish Coast Guard, and Papua New Guinea’s Coast Guard. The OVERSEE project displays vessel information in real-time through AIS messages, which are mandatory for most cargo vessels to report consistently. Anomaly de tection and behavior monitoring tools are computer-based systems that analyse real-time data to detect anomalous behaviors. This project aims to develop a solution capable of detecting anomalous behaviors committed by vessels using AIS messages, which will be re ported in real-time automatically via e-mail and the extant OVERSEE graphical interface. The solution is developed with the use of Long Short-Term Memory Recurrent Neural Net works, and a deeper analysis is provided to compare the obtained results with the ideal results. The network training and testing are done with real data, with cross-classification techniques to improve the trustworthiness of the algorithm, hence providing more accurate results.O tráfego marítimo desempenha um papel muito importante na economia mundial, com mais de 90% do comércio global feito por meio do transporte naval. O grande volume de tráfego de embarcações, principalmente devido ao transporte de cargas, leva a vários novos riscos, ameaças e preocupações, como o aumento da criminalidade no mar. O projeto OVERSEE é um software proprietário desenvolvido pela Critical Software e usado pela Marinha Portuguesa, Guarda Costeira Irlandesa e Guarda Costeira da Papua Nova Guiné. O projeto OVERSEE exibe informações da embarcação em tempo real por meio de mensagens AIS, cuja maioria das embarcações de carga são obrigadas a relatar num período de tempo regular. As ferramentas de detecção de anomalias e monitoramento de comportamento são sistemas baseados em computador que analisam dados em tempo real para detetar comportamentos anómalos. Este projeto visa desenvolver uma solução capaz de detetar comportamentos anómalos cometidos por embarcações por meio de mensagens AIS, que serão reportados em tempo real automaticamente via e-mail e interface gráfica existente do OVERSEE. A solução está desenvolvida com o uso de Redes Neurais Recorrentes1 de Memória-Curta de Longo Prazo2 . Uma análise mais profunda é fornecida para comparar os resultados obtidos com os resultados ideais. O treinamento e teste da rede são feitos com dados reais, com técnicas de classificação cruzada para melhorar a confiabilidade do algoritmo, fornecendo resultados mais precisos