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Multi-criteria decision making for integrated urban water management

WATER RESOURCES MANAGEMENT 2008年第8期22卷 1017-1029页

作者： Zarghami, Mahdi Abrishamchi, Ahmad Ardakanian, Reza Sharif Univ Technol Dept Civil Engn Tehran Iran

The city of Zahedan, in South-eastern Iran, has high population growth, limited local freshwater resources and inadequate water distribution system resulting in water supply failures in recent years. This paper will investigate integration of several demand management measures such as leakage detection on water distribution network, water metering and low volume water fixtures as well as the conjunctive use of surface and groundwater resources of this city. For integration of water management criteria, compromise programming will be used as a multi-objective decision making method. The criteria include minimizing the cost, maximizing water supply and minimizing the social hazards due to the water supply operations. This model will derive optimum long-term plans for implementation of water resources. The results will show that demand management can delay a water transfer project for Zahedan city up to 10 years. compromise programming is as an efficient tool for integrated water resources management in urban areas and the method is capable to being used by decision-makers in other cases.

关键词： compromise programming integrated water resources management long distance water transfer demand management arid regions

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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC

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IEEE ACCESS 2021年 9卷 59093-59107页

作者： Son, Ngo Tung Jaafar, Jafreezal Aziz, Izzatdin Abdul Anh, Bui Ngoc Univ Teknol Petronas Dept Comp & Informat Sci Seri Iskandar 32610 Perak Malaysia FPT Univ Informat & Commun Technol Dept Hanoi 100000 Vietnam

Online learning platforms, such as Coursera, Edx, Udemy, etc., offer thousands of courses with different content. These courses are often of discrete content. It leads the learner not to find a learning path in a vast volume of courses and contents, especially when they have no experience in advance. Streamlining the order of courses to create a well-defined learning path can help e-learners achieve their learning goals effectively and systematically. The learners usually ask the necessary skills that they expect to earn (query). The need is to develop a recommender system that can search for suitable learning paths. This study proposes a multi-objective optimization model as a knowledge-based recommender. Our model can generate an appropriate learning path for learners based on their background and job goals. The recommended studying path satisfies several learner criteria, such as the critical learning path, number of enrollments, learning duration, popularity, rating of previous learners, and cost. We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. Finally, we tested proposed methods with a dataset consisting of Coursera's courses and Vietnam work's jobs. The test results show the effectiveness of the proposed method.

关键词： Optimization Electronic learning Data mining Genetic algorithms Computer aided instruction Java Ant colony optimization Learning path Knowledge-based recommendation Knowledge graph multi-objective optimization compromise programming genetic algorithm ant colony optimization algorithm

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INTERACTIVE compromise HYPERSPHERE METHOD AND ITS APPLICATIONS

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RAIRO-OPERATIONS RESEARCH 2012年第3期46卷 235-252页

作者： Sitarz, Sebastian Univ Silesia Inst Math PL-40007 Katowice Poland

The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of the proposed method are presented in four multi-criteria problems: the assignment problem, the knapsack problem, the project management problem and the manufacturing problem.

关键词： Multi-criteria problems multiple objective linear programming sensitivity analysis decision making compromise programming

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Numerical investigation and optimization of flow and thermal characteristics of nanofluid within a chaotic geometry

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ADVANCED POWDER TECHNOLOGY 2016年第1期27卷 184-192页

作者： Bahiraei, Mehdi Hangi, Morteza Kermanshah Univ Technol Sch Energy Dept Mech Engn Kermanshah Iran Australian Natl Univ Res Sch Engn Canberra ACT 2601 Australia

In this study, hydrothermal characteristics of the water-TiO2 nanofluid are evaluated in the rectangular C-shaped chaotic channel by applying the two-phase Euler-Lagrange method. The results show that the fluid temperature distribution in the C-shaped channel is much more uniform than that in the straight rectangular channel due to the intense mixing in the chaotic geometry. By increasing the concentration and reducing the particle size, both convective heat transfer and pressure drop increase in the chaotic channel. For finer particles, due to more intense particle migration related to the Brownian motion, more uniform concentration distribution is obtained at the channel cross section. The model of mean convective heat transfer coefficient and pressure drop in terms of concentration and particle size was developed by neural network. In order to obtain some cases of the variables (i.e. size and concentration of nanoparticles) in which maximum heat transfer along with minimum pressure drop occurs, optimization on neural network model was implemented using methods of two-objective as well as single-objective (i.e. genetic algorithm coupled with compromise programming decision making method). Eventually, optimum cases were suggested for different importance levels of objective functions. (C) 2015 The Society of Powder Technology Japan. Published by Elsevier B.V. and The Society of Powder Technology Japan. All rights reserved.

关键词： Nanofluid Chaotic geometry Genetic algorithm compromise programming Two-phase simulation

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Optimal collaborative demand-response planner for smart residential buildings

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ENERGY 2018年 161卷 370-380页

作者： Gomez-Herrera, Juan A. Anjos, Miguel F. Polytech Montreal GERAD CP 6079Succ Ctr Ville Montreal PQ H3C 3A7 Canada Polytech Montreal Dept Math & Ind Engn CP 6079Succ Ctr Ville Montreal PQ H3C 3A7 Canada

This work presents a collaborative scheme for the end-users in a smart building with multiple housing units. This approach determines a day-ahead operational plan that provides demand-response services by taking into account the amount of energy consumed per household, the use of shared storage and solar panels, and the amount of shifted load. We use a biobjective optimization model to trade off total user satisfaction versus total cost of energy consumption. The optimization works in combination with a price structure based on time and level of use that encourages load shifting and benefits the participants. Computational experiments and an extensive sensitivity analysis validate the performance of the proposed approach and help to clarify its strengths, its limits, and the requirements for ensuring the desired outcome. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Smart buildings Demand-response Residential load Biobjective optimization compromise programming

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A new normalized goal programming model for multi-objective problems: A case of supplier selection and order allocation

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年 148卷 158-165页

作者： Jadidi, O. Zolfaghari, S. Cavalieri, S. Bergamo Univ Dept Business Adm Bergamo BG Italy Ryerson Univ Dept Mech & Ind Engn Toronto ON M5B 2K3 Canada Univ Bergamo Dept Engn Dalmine BG Italy

This paper models the problem of supplier selection as a multi-objective optimization problem (MOOP) where minimization of price, rejects and lead-time are considered as three objectives. The paper considers two different cases: (1) the crisp MOOP in which the goals of objectives are predetermined;and (2) the fuzzy MOOP in which the weights of objectives are predetermined. In both cases, the aim is to achieve some levels of consistency among different objectives. To do so, a normalized goal programming approach is developed and tested for both cases. In order to compare the effectiveness of the proposed method, a comparative analysis is presented which includes weighted goal programming, compromise programming, TOPSIS, weighted objectives, min-max goal programming and weighted max-min models. An illustrative example reveals that our proposed model is able to achieve the desirable consistency among all objectives. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Multi-objective supplier selection Normalized goal programming compromise programming TOPSIS Weighted goal programming Min-max goal programming Weighted max-min model

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A multi-objective model for the closed-loop supply chain network design with a price-dependent demand, shortage and disruption

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第6期36卷 5261-5272页

作者： Ghomi-Avili, Morteza Khosrojerdi, Amir Tavakkoli-Moghaddam, Reza Iran Univ Sci & Technol Sch Ind Engn Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran USERN Tehran Iran Arts & Metiers ParisTech LCFC Metz France

This paper presents a multi-objective model for the closed-loop supply chain network design (CLSCND) with a price-dependent demand while considering random disruptions and shortage. This network consists of suppliers, production centers, collection/inspection centers, disposal centers, and market zones. In this model, a demand function is assumed to be a function of price offered to the customer by two different linear and exponential forms. Different resilience strategies including lateral transshipment among production centers and multi-source allocation are applied to model the resilient supply chain network design problem. Moreover, the importance of time for costumers is led to consider different transportation methods for fulfilling the customers' demand. Then, three different objective functions were incorporated when shortage is allowed and the unfulfilled demand will be back ordered. Then, a compromise programming method is used to convert the multi-objective model to a single-objective equivalent form. Furthermore, the application of the model is examined in a real industrial case involved in the production and distribution of glass. Finally, and the numerical results arrive at helpful managerial insights.

关键词： Closed-loop supply chain disruption shortage compromise programming uncertainty

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Replicability of Annual and Seasonal Precipitation by CMIP5 and CMIP6 GCMs over East Asia

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KSCE JOURNAL OF CIVIL ENGINEERING 2022年第4期26卷 1978-1989页

作者： Shiru, Mohammed Sanusi Shahid, Shamsuddin Chae, Seung-Taek Chung, Eun-Sung Seoul Natl Univ Sci & Technol Dept Civil Engn Seoul 01811 South Korea Fed Univ Dutse Fac Sci Dept Environm Sci Dutse 7156 Nigeria Univ Teknol Malaysia Dept Water & Environm Engn Johor Baharu 81310 Malaysia

global climate models (GCMs) structure is a source of uncertainty in climate change projections. Therefore, evaluation of the performances of GCMs is crucial for development of adaptation and mitigation measures and risk reduction against climate change impacts. This study quantified the performances of 10 GCMs of the Coupled Model Intercomparison Project 5 (CMIP5) and their CMIP6 equivalents in replicating precipitation over East Asia during 1975-2005. The CMIP5 and CMIP6 GCMs and their multi-model ensembles (MMEs) were annually and seasonally compared with the Global Precipitation Climatology Centre (GPCC) precipitation. compromise programming was used to rank GCMs by aggregating their scores obtained using statistical performance indices. Taylor diagram was used to assess their relative performances and GCMs' ability to replicate seasonal precipitation distribution was evaluated. Results revealed most CMIP6 GCMs' have better replicability of GPCC precipitation than CMIP5 GCMs. The MME mean of the CMIP6 showed better replicability of annual and seasonal GPCC precipitation than that of CMIP5. The CMIP6 MME also showed efficiency in simulating the seasonal precipitation distribution over East Asia. This study indicates improvements of some CMIP5 GCMs in their CMIP6 equivalents over East Asia. Findings from this study can be significant to policy makers and engineers in reducing the uncertainties in prediction of events such as floods and droughts.

关键词： compromise programming CMIP6 East Asia GCMs Statistical indices

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A quantitative method for accounting human opinion, preferences and perceptions in ecosystem management

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2003年第2期68卷 193-205页

作者： Pavlikakis, GE Tsihrintzis, VA Democritus Univ Thrace Dept Environm Engn Lab Ecol Engn & Technol GR-67100 Xanthi Greece

Ecosystem management (EM) is a holistic approach, in which public participation in decision-making, and incorporation of human preferences, needs and perceptions in management plans is a main element. The decision-making from human opinion method (DeMHO), presented here. can be used in EM in selecting the more suitable and socially acceptable management plan, in order to protect or restore an ecosystem. The method focuses on the quantification of the human opinion, preferences and perceptions, which are investigated after research on the local population of the ecosystem. The results of this research are the inputs of the method;multi-criteria decision-making procedures, such as the analytic hierarchy process (AHP), the expected utility method (EUM) and compromise programming (CP) are used to assign the appropriate weights and rank according to their importance the interest groups, the issues to be studied, and the alternative management plans. The alternatives are also evaluated by assessing their sustainable character. The paper presents DeMHO and its application in the National Park of Eastern Macedonia and Thrace in Greece, after a research through a questionnaire on the local population. (C) 2003 Elsevier Science Ltd. All rights reserved.

关键词： ecosystem management public opinion decision-making analytic hierarchy process expected utility method compromise programming research questionnaire

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Designing a resilient competitive supply chain network under disruption risks: A real-world application

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2018年 115卷 87-109页

作者： Ghavamifar, Ali Makui, Ahmad Taleizadeh, Ata Allah Univ Tehran Sch Ind Engn Coll Engn Tehran Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

We address an intra-supply chain competition where a producer and resellers competing to achieve their goals, while taking into consideration the uncertainties and disruption risks. We utilize a bi-level multi-objective programming approach for designing a competitive supply chain network. A hybrid solution approach, combining the compromise programming and Benders decomposition methods, is developed to solve the model. Furthermore, an efficient inequality constraint is proposed to cope with the computational complexity of the bi-level model. To explore the practical application of the model, a real-world case example is discussed. Finally, the scalability of the solution approach is illustrated for large-scale problems.

关键词： Competition Disruption risks Bi-level programming compromise programming Benders decomposition

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