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An integrative case study approach between game theory and Pareto frontier concepts for the transboundary water resources allocations

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JOURNAL OF HYDROLOGY 2012年 450卷 308-319页

作者： Kucukmehmetoglu, Mehmet Gebze Inst Technol Dept City & Reg Planning TR-41400 Gebze Kocaeli Turkey

In the context of transboundary issues, this paper introduces a composite water resources allocation approach that integrates both game theory and Pareto frontier concepts over the case of the Euphrates and Tigris Rivers. The proposed approach searches for an acceptable and viable solution set over the Pareto Frontier Surface via game theory based rationality constraints. For this purpose, the used base model is the Euphrates and Tigris River Basin Model, which is a linear programming model maximizing net economic benefits while optimally allocating scarce water resources in the basin. Results indicate that game theory based strategies and associated constraints provide a determinative backbone for an efficient and effective use of generated Pareto Frontier Surfaces. Additionally, estimated marginal values imply that the upstream countries have upper hand positions regarding their geographic and climatic contexts. After all the generation schemes, it appears that Turkey is the critical partner for inclusion into any form of coalition in the Euphrates and Tigris River Basin. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Linear programming multi-objective programming Game theory Pareto Frontier Surface Transboundary water resources allocation The Euphrates and Tigris

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Resilience Optimization for Complex Engineered Systems Based on the multi-Dimensional Resilience Concept

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IEEE ACCESS 2017年 5卷 19352-19362页

作者： Ren, Fuchun Zhao, Tingdi Jiao, Jian Hu, Yuqing Beihang Univ Sch Reliabil & Syst Engn Beijing 100191 Peoples R China

Most traditional engineered systems are designed with a passive and fixed reliability capability and just required to achieve a possibly low level of failure occurrence. However, as the complexity at spatial-temporal scales and integrations increases, modern complex engineered systems (CESs) are facing new challenges of inherent risk and bottleneck for a successful and safe operation through the system life cycle when potential expected or unexpected disruptive events happen. As a prototype for ensuring the successful operation of inherently risky systems, resilience has demonstrated itself to be a promising concept to address the above-mentioned challenges. A standard multi-dimensional resilience triangle model is first presented based on the concept of the three-phase system resilience cycle, which can provide a theoretical foundation for indicating the utility objectives of resilience design. Then, the resilience design problem for CESs is proposed as a multi-objective optimization model, in which the three objectives are to maximize the survival probability, to maximize the reactive timeliness and to minimize the total budgeted cost. Furthermore, the proposed multi-objective optimization programming is solved based on the efficient multi-objective evolutionary algorithm NSGA-II. Finally, the effectiveness of the proposed models and solving procedure is illustrated with an engineered electro-hydrostatic aircraft control actuator resilience design problem, a comparative analysis on the case study is also carried out with respect to previous works. This work can provide an effective tradeoff foundation to improve the resilience of CESs.

关键词： Resilience complex engineered systems multi-dimensional model multi-objective programming NSGA-II

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Robust bi-objective macroscopic municipal water supply network redesign and rehabilitation

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WATER RESOURCES MANAGEMENT 2017年第9期31卷 2689-2711页

作者： Naderi, M. J. Pishvaee, M. S. Iran Univ Sci & Technol Sch Ind Engn Tehran Iran

Water companies traditionally deal with the problem of rehabilitation and redesign of municipal water supply system due to the either of aging the existed water supply network and housing development. However, such problems are hemmed in by uncertainty due to their long planning horizons and the fact that the exact prediction of future is impossible. Uncertain data and parameters which are likely to undermine the effectiveness of our decisions in this area, are exacerbated if they are be correlated. Unfortunately, correlated uncertain parameters are the things typically such problems are entangled with. Thus, along with considering all of decision objectives, it is incumbent upon water supply system redesign and rehabilitation decision model to develop methods able to appropriately confront with the correlated uncertainty. This paper introduces a bi-objective robust optimization model capable of handling correlated uncertain parameters in municipal water supply system redesign and rehabilitation problem. This robust optimization framework is able to adjust the level of conservatism, a factor which contributes to the reliability of the system. The proposed mathematical framework is applied for a water supply system inspired from Tehran potable water supply system and then various levels of conservatism and reliability are compared. Numerical results show neglecting uncertainty can lead to significant increase in the total cost and amount of unsatisfied demand.

关键词： Municipal water supply systemredesign Leakagemanagement Reliability Correlated robust optimization multi-objective programming

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Designing a robust demand-differentiated platelet supply chain network under disruption and uncertainty

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2020年第8期11卷 3231-3258页

作者： Yaghoubi, Saeed Hosseini-Motlagh, Seyyed-Mahdi Cheraghi, Sara Larimi, Niloofar Gilani Iran Univ Sci & Technol Sch Ind Engn Tehran Iran

Managing platelets supply chain network has proved challenging. Besides stochastic demand, the high perishability of platelets and the diversity of their demands make the management more intricate. As a motivation to conduct this paper, we investigate a real-world case study facing a variety of platelet demands to satisfy. Being the first-ever study, we contribute a practical method for the efficient design and planning of a multiple platelet-derived products supply chain network. As the most perishable blood product, platelets need to be maintained fresh. Thus, we suggest a bi-objective model make a tradeoff relationship between the network costs and platelets' freshness. Further, we account for two realistic features that the products are categorized into three main types with respect to their application and lifetime, and hospitals are prioritized based on their specialty and the population of patients they cover. To cope with the uncertainty and objective multiplicity, we develop a mixed approach. The network robustness under uncertainty is controlled by a robust method and the Pareto solutions of the conflicting objectives are obtained via an interactive approach. Further, we take into account real-world scenarios that the network facilities may face disruptions and utilize a robust scenario-based approach to deal with the disruption scenarios. The results demonstrate that although simultaneous demand fluctuation and disruption increase both logistics costs and delivery time, the proposed model is capable of achieving robust solutions that a little increase in the logistic costs obtains a considerable reduction in the level of relative regret. Further, the network will benefit from a favorable saving in the logistic costs only by a little increase in the storage time.

关键词： Platelet supply chain multi-product multi-objective programming Robust optimization Disruption

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A set optimization approach to zero-sum matrix games with multi-dimensional payoffs

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MATHEMATICAL METHODS OF OPERATIONS RESEARCH 2018年第3期88卷 369-397页

作者： Hamel, Andreas H. Loehne, Andreas Free Univ Bozen Bolzano Fac Econ & Management Bolzano Italy Friedrich Schiller Univ Dept Math Jena Germany

A new solution concept for two-player zero-sum matrix games with multi-dimensional payoffs is introduced. It is based on extensions of the vector order in , so-called set relations, and strictly motivated by the interpretation of the payoff as multi-dimensional loss for one and gain for the other player. The new concept provides coherent worst case estimates for games with multi-dimensional payoffs. It is shown that-in contrast to games with one-dimensional payoffs-the corresponding strategies are different from equilibrium strategies for games with multi-dimensional payoffs. The two concepts are combined into new equilibrium notions for which existence theorems are given. Relationships of the new concepts to existing ones such as Shapley and vector equilibria, vector minimax and maximin solutions as well as Pareto optimal security strategies are clarified.

关键词： Zero-sum game multi-dimensional payoff multi-objective programming Set relation Set optimization Incomplete preference

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Mathematical analyses of ecological and economic tradeoffs in irrigated agriculture based on inexact optimization principles and hierarchical crop projections

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JOURNAL OF CLEANER PRODUCTION 2019年 235卷 69-84页

作者： Zhang, Shan Tan, Qian Cai, Yanpeng Zhang, Tong Song, Ge China Agr Univ Coll Water Resources & Civil Engn Beijing 100083 Peoples R China Guangdong Univ Technol Inst Environm & Ecol Engn Guangzhou 510006 Guangdong Peoples R China Beijing Normal Univ State Key Lab Water Environm Simulat Beijing 100875 Peoples R China

An entropy-based multi-objective interval stochastic programming (EMISP) approach based on interval hierarchical projection, interval information entropy, interval analysis and chance-constrained programming was developed for supporting agricultural water management. EMISP improved upon existing methods through measuring and balancing ecological and economic benefits of irrigated croplands under uncertainty. To demonstrate its applicability, the developed method has been applied to an arid Chinese watershed. The results suggested that grain crops would produce higher ecological benefits than economic crops. A series of benefit- and risk-explicit plans for agricultural water use were generated, which indicated that the relaxation of water availability constraints would generate higher comprehensive benefits, but increase the risks of system infeasibility. The results from the EMISP model were also compared to those from four potential alternative models. These comparisons revealed that EMISP could achieve higher water productivity and comprehensive benefits with controllable water-shortage risks. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： multi-objective programming Information entropy Uncertainty analysis Mathematical optimization Agricultural water management Ecological functions

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Using the idea of expanded core for the exact solution of bi-objective multi-dimensional knapsack problems

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JOURNAL OF GLOBAL OPTIMIZATION 2011年第4期49卷 589-606页

作者： Mavrotas, George Figueira, Jose Rui Antoniadis, Alexandros Natl Tech Univ Athens Athens 15780 Greece Inst Super Tecn Dept Engn & Gestao P-2780990 Porto Salvo Portugal

We propose a methodology for obtaining the exact Pareto set of Bi-objective multi-Dimensional Knapsack Problems, exploiting the concept of core expansion. The core concept is effectively used in single objective multi-dimensional knapsack problems and it is based on the "divide and conquer" principle. Namely, instead of solving one problem with n variables we solve several sub-problems with a fraction of n variables (core variables). In the multi-objective case, the general idea is that we start from an approximation of the Pareto set (produced with the multi-Criteria Branch and Bound algorithm, using also the core concept) and we enrich this approximation iteratively. Every time an approximation is generated, we solve a series of appropriate single objective Integer programming (IP) problems exploring the criterion space for possibly undiscovered, new Pareto Optimal Solutions (POS). If one or more new POS are found, we appropriately expand the already found cores and solve the new core problems. This process is repeated until no new POS are found from the IP problems. The paper includes an educational example and some experiments.

关键词： Knapsack problem multi-objective programming Core Exact algorithm

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Portfolio optimization using elliptic entropy and semi-entropy of coherent fuzzy numbers

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INFORMATION SCIENCES 2022年 614卷 240-262页

作者： Gupta, Pankaj Univ Delhi Dept Operat Res Delhi 110007 India

This paper explores the elliptic entropy and the elliptic semi-entropy of a coherent fuzzy number and discusses several of their properties. We propose a methodology that incorporates the adaptive index, k, of the coherent fuzzy number representing an individual investor's stock market assessment (pessimistic, optimistic, or neutral). We combine the adaptive index with the elliptic entropy and semi-entropy to obtain risk measures incorporating investor attitude. We use the proposed risk measures in a portfolio optimization problem that uses coherent fuzzy numbers to model the asset returns. The optimization models are solved using a genetic algorithm. We apply the proposed methodology to a large-scale case study involving 100 assets to demonstrate its effectiveness. The realworld performance of the proposed approach is illustrated using an out-of-sample analysis. Based on the results we obtained, we discuss the advantages and disadvantages of elliptic entropy and semi-entropy. Finally, we compare the proposed methodology with other approaches in the literature and demonstrate its superiority. (c) 2022 Elsevier Inc. All rights reserved.

关键词： Fuzzy portfolio optimization Credibility theory Coherent fuzzy numbers Elliptic entropy Elliptic semi-entropy multi-objective programming Genetic algorithm

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A TWO-STAGE SOLUTION APPROACH FOR PLASTIC INJECTION MACHINES SCHEDULING PROBLEM

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2021年第3期17卷 1289-1314页

作者： Sarac, Tugba Sipahioglu, Aydin Ozer, Emine Akyol Eskisehir Osmangazi Univ Dept Ind Engn Meselik Campus TR-26040 Eskisehir Turkey Eskisehir Tech Univ Dept Ind Engn Iki Eylul Campus TR-26555 Eskisehir Turkey

One of the most common plastic manufacturing methods is injection molding. In injection molding process, scheduling of plastic injection machines is very difficult because of the complex nature of the problem. For example, similar plastic parts should be produced sequentially to prevent long setup times. On the other hand, to produce a plastic part, its mold should be fixed on an injection machine. Machine eligibility restrictions should be considered because a mold can be usually fixed on a subset of the injection machines. Some plastic parts which have same shapes but different colors are used same mold so these parts can only be scheduled simultaneously if their mold has copies, otherwise resource constraints should be considered. In this study, a multi-objective mathematical model is proposed for parallel machine scheduling problem to minimize makespan, total tardiness, and total waiting time. Since NP-hard nature of problem, this paper presents a two-stage mathematical model and a two-stage solution approach. In the first stage of mathematical model, jobs are assigned to the machines and each machine is scheduled separately in the second stage. The integrated model and two-stage mathematical model are scalarized by using goal programming, compromise programming and Lexicographic Weighted Tchebycheff programming methods. To solve large-scale problems in a short time, a two-stage solution approach is also proposed. In the first stage of this approach, jobs are assigned to machines and scheduled by using proposed simulated annealing algorithm. In the second stage of the approach, starting time, completion time and waiting time of the jobs are calculated by using a mathematical model. The performance of the methods is demonstrated on randomly generated test problems.

关键词： Plastic injection identical parallel machine scheduling multi-objective programming integer programming

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A methodology for assessing eco-efficiency in logistics networks

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2009年第3期193卷 670-682页

作者： Frota Neto, J. Quariguasi Walther, G. Bloemhof, J. van Nunen, J. A. E. E. Spengler, T. Erasmus Univ Rotterdam Sch Management RSM NL-3000 DR Rotterdam Netherlands Tech Univ Carolo Wilhelmina Braunschweig Inst Econ & Business Adm Braunschweig Germany

Recent literature on sustainable logistics networks points to two important questions: (i) How to spot the preferred solution(s) balancing environmental and business concerns? (ii) How to improve the understanding of the trade-offs between these two dimensions? We posit that a visual exploration of the efficient frontier and trade-offs between profitability and environmental impacts are particularly suitable to answer these two questions. The visual representation of the efficient frontier, however, presents two challenges. The first is to obtain a good approximation for such frontier without enumerating all extreme efficient solutions. The second is to obtain a good visual representation of the efficient frontier. We propose a two-phased heuristic to handle these two problems. The algorithm is designed for the multi-objective linear problem with three objectives: minimize costs, cumulative energy demand and waste in a reverse logistics network. We illustrate our approach by designing a complex recycling logistics network in Germany. (C) 2007 Elsevier B.V. All rights reserved.

关键词： Eco-efficiency Sustainable supply chains Closed-loop supply chains multi-objective programming Optimization

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