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Solving binary-state multi-objective reliability redundancy allocation series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2012年 103卷 35-44页

作者： Khalili-Damghani, Kaveh Amiri, Maghsoud Islamic Azad Univ Dept Ind Engn S Tehran Branch Tehran Iran Allameh Tabatabai Univ Ind Management Dept Management & Accounting Fac Tehran Iran

In this paper, a procedure based on efficient epsilon-constraint method and data envelopment analysis (DEA) is proposed for solving binary-state multi-objective reliability redundancy allocation series-parallel problem (MORAP). In first module, a set of qualified non-dominated solutions on Pareto front of binary-state MORAP is generated using an efficient epsilon-constraint method. In order to test the quality of generated non-dominated solutions in this module, a multi-start partial bound enumeration algorithm is also proposed for MORAP. The performance of both procedures is compared using different metrics on well-known benchmark instance. The statistical analysis represents that not only the proposed efficient epsilon-constraint method outperform the multi-start partial bound enumeration algorithm but also it improves the founded upper bound of benchmark instance. Then, in second module, a DEA model is supplied to prune the generated non-dominated solutions of efficient epsilon-constraint method. This helps reduction of non-dominated solutions in a systematic manner and eases the decision making process for practical implementations. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： epsilon-constraint method Pareto front Multi-objective redundancy allocation problem DEA

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New optimized configuration for a hybrid PV/diesel/battery system based on coyote optimization algorithm: A case study for Hotan county

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ENERGY REPORTS 2022年 8卷 15480-15492页

作者： Sari, Arif Majdi, Ali Opulencia, Maria Jade Catalan Timoshin, Anton Dinh Tran Ngoc Huy Nguyen Dinh Trung Alsaikhan, Fahad Hammid, Ali Thaeer Akhmedov, Abdulaziz Girne Amer Univ Dept Management Informat Syst Via Mersin 10 Kyrenia North Cyprus Turkey Al Mustaqbal Univ Coll Dept Bldg & Construct Tech Hilla Iraq Ajman Univ Coll Business Adm Ajman U Arab Emirates Sechenov Univ IM Sechenov First Moscow State Med Univ Dept Propaedeut Dent Dis Moscow Russia Banking Univ HCMC Ho Chi Minh City Ho Chi Minh City Vietnam Int Univ Japan Niigata Japan NEU Hanoi Vietnam Prince Sattam Bin Abdulaziz Univ Clin Pharm Dept Clin Pharm Coll Pharm Alkharj Saudi Arabia Imam Jaafar Al Sadiq Univ Dept Comp Engn Baghdad Iraq Dept Informat & Teaching Methods Bunyodkor St 27 Tashkent Uzbekistan

The main objective of this study is to present a multi-objective and optimal hybrid PV/diesel generator/battery Renewable Energy System (HRES) to provide this reliability in the Hotan county, placed in Taklamakan Desert. This study uses the epsilon-constraint method along with a developed version of the coyote optimization algorithm to achieve the best values of the component sized to decrease the loss of load probability, CO2 emission value, and the annualized cost of the system. Sensitivity analysis also is performed to show each component's impact on the system. The results demonstrate that the DG backup system improves the yearly cost of the system from 8347.2 $ to 9318.4 $, which shows about 10.42% increasing by increasing the fuel consumption. Here, the LLP increases from 0% to 9.19% and the CO2 emissions improve from 2531.2 kg/yr to 13257 kg/yr. Accordingly, the COE value is reduced from 0.39 $/kWh to 0.24 $/kWh over the PV penetration, reducing from 92.27% to 59.42%. This decreasing indicates that the system fuel cost has more impact than the cost of PV on the COE, which is due to the low cost required of conventional power production than the PV system. The results also indicate a noteworthy upshot on the battery storage unit size such that the size of epsilon(CO2) has been enhanced from 27.4 kWh to 50 kWh in the range from 7000 kg/year to 25 kg/year. The results also are compared with the PSO-based optimal system and HOMER software results to show its excellence toward them. (c) 2022 The Author(s). Published by Elsevier Ltd.

关键词： Hybrid renewable energy system Multi-objective optimization Taklamakan desert epsilon-constraint method Sensitivity analysis HOMER Coyote optimization algorithm Improved

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ε-OA for the solution of bi-objective generalized disjunctive programming problems in the synthesis of nonlinear process networks

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COMPUTERS & CHEMICAL ENGINEERING 2015年 72卷 199-209页

作者： Fattahi, Ali Turkay, Metin Koc Univ Dept Ind Engn TR-34450 Istanbul Turkey

There has been an increasing interest in multicriteria optimization (MCO) of nonlinear process network problems in recent years. Several mathematical models have been developed and solved using MCO methodologies including e-constraint, weighted sum, and minimum distance. In this paper, we investigate the bi-objective nonlinear network synthesis problem and propose an effective algorithm, epsilon-OA, based on augmented epsilon-constraint and logic-based outer approximation (OA). We provide theoretical characterization of the proposed algorithm and show that the solutions generated are efficient. We illustrate the effectiveness of our novel algorithm on two benchmark problems. The epsilon-OA is compared to the straightforward use of OA with augmented epsilon-constraint algorithm (epsilon-con + OA), the augmented epsilon-constraint without OA (E-MINLP), and the traditional epsilon-constraint (T-epsilon-con). Based on the results, our novel algorithm is very effective in solving the bi-objective generalized disjunctive programming problems in the synthesis of process networks. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Generalized disjunctive programming Multiple criteria optimization Outer approximation Mixed integer nonlinear programming epsilon-constraint method

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Optimal design of CHP-based microgrids: Multiobjective optimisation and life cycle assessment

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ENERGY 2015年 85卷 181-193页

作者： Zhang, Di Evangelisti, Sara Lettieri, Paola Papageorgiou, Lazaros G. UCL Dept Chem Engn London WC1E 7JE England

As an alternative to current centralised energy generation systems, microgrids are adopted to provide local energy with lower energy expenses and gas emissions by utilising distributed energy resources (DER). Several micro combined heat and power technologies have been developed recently for applications at domestic scale. The optimal design of DERs within CHP-based microgrids plays an important role in promoting the penetration of microgrid systems. In this work, the optimal design of microgrids with CHP units is addressed by coupling environmental and economic sustainability in a multi-objective optimisation model which integrates the results of a life cycle assessment of the microgrids investigated. The results show that the installation of multiple CHP technologies has a lower cost with higher environmental saving compared with the case when only a single technology is installed in each site, meaning that the microgrid works in a more efficient way when multiple technologies are selected. In general, proton exchange membrane (PEM) fuel cells are chosen as the basic CHP technology for most solutions, which offers lower environmental impacts at low cost. However, internal combustions engines (ICE) and Stirling engines (SE) are preferred if the heat demand is high. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Microgrids Life cycle assessment Multi-objective optimisation epsilon-constraint method Weighted sum

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A New Bi-Objective Approach for Optimal Sizing of Electrical and Thermal Devices in Zero Energy Buildings Considering Environmental Impacts

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2021年第2期12卷 886-896页

作者： Mehrtash, Mahdi Capitanescu, Florin Heiselberg, Per Kvols Gibon, Thomas ERIN Luxembourg Inst Sci & Technol LIST L-4422 Belvaux Luxembourg Univ British Columbia Fac Appl Sci Vancouver BC V6T 1Z2 Canada Aalborg Univ Dept Civil Engn DK-9220 Aalborg OST Denmark

This paper proposes a new bi-objective optimization model, trading-off cost and environmental impacts, for sizing the key electrical and thermal devices in a zero energy building (ZEB), i.e., a building that roughly generates as much renewable energy as it consumes annually. A salient novel feature is the consideration of the environmental impacts, computed through a rigorous life cycle assessment approach, of buying electricity from the grid and manufacturing devices. Furthermore, an enhancement of the proposed model, as compared to the existing models, is to prioritize storing the ZEB excess of energy rather than selling it to the grid. The proposed solution approach of the initial mixed-integer nonlinear programming model relies on McCormick relaxation linearization to obtain a more tractable mixed-integer linear model. An augmented epsilon-constraint method is applied to solve the obtained bi-objective model. Finally, considering the building owners' willingness-to-pay for environmental impacts, a decision-making criterion is proposed to select the optimal size of the devices among all non-dominated solutions of the Pareto front.

关键词： Environmental impacts McCormick relaxation mixed-integer linear programming multi-objective optimization zero energy building epsilon-constraint method

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Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2013年第2期41卷 369-382页

作者： Liu, Songsong Papageorgiou, Lazaros G. UCL Dept Chem Engn Ctr Proc Syst Engn London WC1E 7JE England

The performance of a supply chain should usually be measured by multiple criteria. We address production, distribution and capacity planning of global supply chains considering cost, responsiveness and customer service level simultaneously. A multiobjective mixed-integer linear programming (MILP) approach is developed with total cost, total flow time and total lost sales as key objectives. Also, two strategies to expand the formulation plants' capacities are considered in the model. The epsilon-constraint method and lexicographic minimax method are used as solution approaches to tackle the multiobjective problem. Finally, a numerical example is investigated to demonstrate the applicability of the proposed model and solution approaches. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Multiobjective optimisation Global supply chains MILP epsilon-constraint method Lexicographic minimax method Pareto-optimal solutions

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Multi-Objective Reconfiguration of Radial Distribution Systems Using Reliability Indices

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IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第2期31卷 1048-1062页

作者： Paterakis, Nikolaos G. Mazza, Andrea Santos, Sergio F. Erdinc, Ozan Chicco, Gianfranco Bakirtzis, Anastasios G. Catalao, Joao P. S. Univ Beira Interior Covilha Portugal Univ Lisbon IST INESC ID P-1699 Lisbon Portugal Politecn Torino Dept Energy Power & Energy Syst Unit I-10129 Turin Italy Yildiz Tech Univ Dept Elect Engn Istanbul Turkey Aristotle Univ Thessaloniki GR-54006 Thessaloniki Greece

This paper deals with the distribution network reconfiguration problem in a multi-objective scope, aiming to determine the optimal radial configuration by means of minimizing the active power losses and a set of commonly used reliability indices formulated with reference to the number of customers. The indices are developed in a way consistent with a mixed-integer linear programming (MILP) approach. A key contribution of the paper is the efficient implementation of the epsilon-constraint method using lexicographic optimization in order to solve the multi-objective optimization problem. After the Pareto efficient solution set is generated, the resulting configurations are evaluated using a backward/forward sweep load-flow algorithm to verify that the solutions obtained are both non-dominated and feasible. Since the epsilon-constraint method generates the Pareto front but does not incorporate decision maker (DM) preferences, a multi-attribute decision making procedure, namely, the technique for order preference by similarity to ideal solution (TOPSIS) method, is used in order to rank the obtained solutions according to the DM preferences, facilitating the final selection. The applicability of the proposed method is assessed on a classical test system and on a practical distribution system.

关键词： Distribution system reconfiguration epsilon-constraint method loss minimization mixed-integer linear programming multi-objective optimization reliability

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Exploring the trade-off between competing objectives for electricity energy retailers through a novel multi-objective framework

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ENERGY CONVERSION AND MANAGEMENT 2015年第Feb.期91卷 12-18页

作者： Charvvand, Mansour Ahmadi, Abdollah Siano, Pierluigi Dargahi, Vahid Sarno, Debora HEPDC Bandar Abbas Iran Univ New S Wales Sch Elect Engn & Telecommun Sydney NSW Australia Univ Salerno Dept Ind Engn Fisciano Italy Clemson Univ Holcombe Dept Elect & Comp Engn Microgrid & Power Elect Lab Clemson SC 29634 USA

Energy retailer is the intermediary between Generation Companies and consumers. In the medium time horizon, in order to gain market share, he has to minimize his selling price while looking at the profit, which is dependent on the revenues from selling and the costs to buy energy from forward contracts and participation in the market pool. In this paper, the two competing objectives are engaged proposing a new multi-objective framework in which a epsilon-constraint mathematical technique is used to produce the Pareto front (set of optimal solutions). The stochasticity of energy prices in the market and customer load demand are coped with the Lattice Monte Carlo Simulation (LMCS) and the method of the roulette wheel, which allow the stochastic multi-objective problem to be turned into a set of deterministic equivalents. The method performance is tested into some case studies. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Energy retailer Forward contracts Multi-objective mathematical programming epsilon-constraint method

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Threshold robustness in discrete facility location problems: a bi-objective approach

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OPTIMIZATION LETTERS 2015年第7期9卷 1297-1314页

作者： Carrizosa, Emilio Ushakov, Anton Vasilyev, Igor Univ Seville Inst Matemat E-41012 Seville Spain Russian Acad Sci Siberian Branch Matrosov Inst Syst Dynam & Control Theory Irkutsk 664033 Russia

The two best studied facility location problems are the -median problem and the uncapacitated facility location problem (Daskin, Network and discrete location: models, algorithms, and applications. Wiley, New York, 1995;Mirchandani and Francis, Discrete location theory. Wiley, New York, 1990). Both seek the location of the facilities minimizing the total cost, assuming no uncertainty in costs exists, and thus all parameters are known. In most real-world location problems the demand is not certain, because it is a long-term planning decision, and thus, together with the minimization of costs, optimizing some robustness measure is sound. In this paper we address bi-objective versions of such location problems, in which the total cost, as well as the robustness associated with the demand, are optimized. A dominating set is constructed for these bi-objective nonlinear integer problems via the -constraint method. Computational results on test instances are presented, showing the feasibility of our approach to approximate the Pareto-optimal set.

关键词： Discrete facility location Robustness Bi-objective combinatorial optimization p-Median problem UFLP epsilon-constraint method delta-Dominating set

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Bi-objective cyclic scheduling for single hoist with processing-time-window constraints considering buffer-setting

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2019年第2期233卷 192-203页

作者： Gao, Zhongshun Zhou, Binghai Tongji Univ Sch Mech Engn Shanghai 201804 Peoples R China

To solve the scheduling problem of a single hoist with processing-time-window constraints considering buffer-setting, we consider bi-objective scheduling which makes trade-offs between the cycle time and the hoist travel distance. First, a bi-objective mixed-integer programming model is constructed for the basic line without considering buffer-setting. In order to improve the throughput of the basic line, a transform method with buffer-setting is put forward. Based on the basic line model, a subsection searching epsilon-constraint method which combines the transform method is introduced to solve the bi-objective mixed-integer programming model. Experimental results both on benchmark instances and on randomly generated instances indicate that the proposed approach is efficient and buffers can improve the throughputs.

关键词： Bi-objective buffer-setting epsilon-constraint method hoist-scheduling problem mixed-integer programming

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