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Mathematical programming techniques in water network optimization

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第3期243卷 774-788页

作者： D'Ambrosio, Claudia Lodi, Andrea Wiese, Sven Bragalli, Cristiana Ecole Polytech CNRS F-91128 Palaiseau France Ecole Polytech LIX F-91128 Palaiseau France Univ Bologna DEI I-40136 Bologna Italy Univ Bologna DICAM I-40136 Bologna Italy

In this article we survey mathematical programming approaches to problems in the field of drinking water distribution network optimization. Among the predominant topics treated in the literature, we focus on two different, but related problem classes. One can be described by the notion of network design, while the other is more aptly termed by network operation. The basic underlying model in both cases is a nonlinear network flow model, and we give an overview on the more specific modeling aspects in each case. The overall mathematical model is a mixed integer nonlinear Program having a common structure with respect to how water dynamics in pipes are described. Finally, we survey the algorithmic approaches to solve the proposed problems and we discuss computation on various types of water networks. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Networks mixed integer nonlinear programming Combinatorial optimization Global optimization

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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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Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-21页

作者： Sun, Yan Lang, Maoxiang Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China Beijing Jiaotong Univ MOE Key Lab Urban Transportat Complex Syst Theory Beijing 100044 Peoples R China

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing;(2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services;(3) carbon dioxide emissions consideration;and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

关键词： multi-modal routing multi-commodity flow schedule-based service time-flexible service mixed integer nonlinear programming linearization method

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Bus schedule coordination for the last train service in an intermodal bus-and-train transport network

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2015年 60卷 360-376页

作者： Dou, Xueping Meng, Qiang Guo, Xiucheng Southeast Univ Sch Transportat Nanjing 210096 Jiangsu Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

Only when a designated bus arrives at a particular bus stop (that connects to a rail station) earlier than the departure time of the associated last train by at least the necessary transfer walking time can passengers on the designated bus successfully access the rail network and finish the remainder of their trips by train. This paper first proposes an optimal bus schedule coordination problem for last train service in an intermodal bus-and-train transport network by offsetting and perturbing the original bus schedules to reduce transfer failures from bus service to train service based on the given last train schedules. The proposed problem is then formulated as a mixed integer nonlinear programming (MINLP) model. The MINLP model is equivalently transformed into a mixed integer linear programming (MILP) model that can be exactly solved by any optimization solvers, such as CPLEX. A case study based on eight real bus lines and the mass rapid transit (MRT) system in Singapore is conducted, and it shows that the bus schedule coordinated by the developed model is able to improve operational intermodal connectivity substantially. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Intermodal bus-and-train network Bus schedule coordination Last train Bus blockage mixed integer nonlinear programming mixed integer linear programming

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The Robust Cold Standby Redundancy Allocation in Series-Parallel Systems With Budgeted Uncertainty

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IEEE TRANSACTIONS ON RELIABILITY 2015年第2期64卷 799-806页

作者： Feizollahi, Mohammad Javad Soltani, Roya Feyzollahi, Hadi Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA Islamic Azad Univ Dept Ind Engn Sci & Res Branch Tehran Iran SUNY Buffalo Dept Ind & Syst Engn Buffalo NY 14260 USA

This paper studies a redundancy allocation problem (RAP) with cold standby strategy in non-repairable series-parallel systems. We assume that the components' reliabilities are uncertain values in a budgeted uncertainty set, with unknown probability distributions. Because the system reliability is a nonlinear function of the components' reliabilities, classical robust optimization approaches cannot be directly applied to construct the robust counterpart of this problem. Therefore, this paper for the first time proposes linear mixed integer programming (MIP) and binary equivalent models for the cold standby RAP;and by exploiting the problem structure, robust counterparts are developed to deal with budgeted uncertainty in this problem. Then, two exact solution methods are proposed: one of them solves a MIP model iteratively in a Benders' decomposition framework, and the other one solves a single binary linear model. The validity and the performance of the proposed approach are tested through a Monte Carlo simulation, and computational results.

关键词： Budgeted uncertainty cold standby redundancy allocation mixed integer nonlinear programming robust optimization series-parallel system

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Derivative-Free Methods for mixed-integer Constrained Optimization Problems

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2015年第3期164卷 933-965页

作者： Liuzzi, Giampaolo Lucidi, Stefano Rinaldi, Francesco CNR Ist Analisi Sistemi & Informat IASI A Ruberti I-00185 Rome Italy Univ Roma La Sapienza Dipartimento Informat & Sistemist A Ruberti I-00185 Rome Italy Univ Padua Dipartimento Matemat I-35121 Padua Italy

Methods which do not use any derivative information are becoming popular among researchers, since they allow to solve many real-world engineering problems. Such problems are frequently characterized by the presence of discrete variables, which can further complicate the optimization process. In this paper, we propose derivative-free algorithms for solving continuously differentiable mixed integer nonlinear programming problems with general nonlinear constraints and explicit handling of bound constraints on the problem variables. We use an exterior penalty approach to handle the general nonlinear constraints and a local search approach to take into account the presence of discrete variables. We show that the proposed algorithms globally converge to points satisfying different necessary optimality conditions. We report a computational experience and a comparison with a well-known derivative-free optimization software package, i.e., NOMAD, on a set of test problems. Furthermore, we employ the proposed methods and NOMAD to solve a real problem concerning the optimal design of an industrial electric motor. This allows to show that the method converging to the better extended stationary points obtains the best solution also from an applicative point of view.

关键词： mixed integer nonlinear programming Derivative-free optimization nonlinear constrained optimization

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Optimal design of microalgae-based biorefinery: Economics, opportunities and challenges

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APPLIED ENERGY 2015年 150卷 69-79页

作者： Rizwan, Muhammad Lee, Jay H. Gani, Rafiqul Korea Adv Inst Sci & Technol Dept Chem & Biomol Engn Taejon 305701 South Korea Tech Univ Denmark Dept Chem & Biochem Engn CAPEC DK-2800 Lyngby Denmark

Microalgae have great potential as a feedstock for the production of a wide range of end-products under the broad concept of biorefinery. In an earlier work, we proposed a superstructure based optimization model to find the optimal processing pathway for the production of biodiesel from microalgal biomass, and identified several challenges with the focus being on utilizing lipids extracted microalgal biomass for economic and environmentally friendly production of useful energy products. In this paper, we expand the previous optimization framework by considering the processing of microalgae residue previously treated as wastes. We develop an expanded biorefinery superstructure model, based on which a mixed integer nonlinear programming (MINLP) model is proposed to determine the optimal/promising biorefinery configurations with different choices of objective functions. The MINLP model is solved in GAMS using a database built in Excel. Economic sensitivity analysis is performed to elaborate the potential improvements in the overall economics, and set the targets that must be achieved in the future in order for microalgal biofuels to become economically viable. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Microalgal biorefinery Biofuels Superstructure optimization mixed integer nonlinear programming Lipid-extracted microalgae

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Distributed Generation Long-Term Planning in Smart Distribution Systems Considering Daily Optimal Operation

Distributed Generation Long-Term Planning in Smart Distribut...

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IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Sindi, Hatem Shaaban, Mostafa El-Saadany, Ehab Univ Waterloo Dept Elect & Comp Engn Waterloo ON Canada Independent Elect Syst Operator Toronto ON Canada

ISBN: (纸本)9781467379335

An algorithm to maximize distributed generation (DG) hosting capacity in a system while lowering overall system cost is proposed in this paper. This algorithm considers several realistic aspects of long-term DG planning, such as cost effective design of feeder reinforcement. It allocates DGs and provides the type, size, location, and year of installation. Both dispatchable and non-dispatchable DG technologies are used. The complexity of the problem necessitates modeling the problem as mixed integer nonlinear programming. This is performed while considering the daily optimal operation of the allocated DGs. A case study of a test system was conducted over a planning period of 20 years, with every year consisting of eight-day patterns and each day having 24 varying hours.

关键词： distributed power generation integer programming nonlinear programming power generation planning daily optimal operation distributed generation long-term planning feeder reinforcement mixed integer nonlinear programming smart distribution systems Distributed power generation Fuels Indexes Planning Reactive power Resource management Yttrium distributed power generation dispensing system Power generation planning nonlinear programming Reactive power Rare earths yttrium integer programming management of resources Fuels Optimal operation mixed integer linear programming

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Piecewise Linear Formulations for Downlink Wireless OFDMA Networks 12th

Piecewise Linear Formulations for Downlink Wireless OFDMA Ne...

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12th International Conference on Mobile Web and Intelligent Information Systems (MobiWis)

作者： Adasme, Pablo Lisser, Abdel Univ Santiago Chile Dept Ingn Elect Santiago 3519 Chile Univ Paris 11 Lab Rech Informat F-91190 Orsay France

ISBN: (纸本)9783319231440;9783319231433

In this paper, we propose piecewise mixed integer linear programming (PWMIP) models for joint subcarrier and power allocation in downlink wireless orthogonal frequency division multiple access (OFDMA) networks. In particular, we consider the problem of maximizing the total capacity of an OFDMA system subject to user power, subcarrier and quality of service constraints. For this purpose, we model the problem as a (0-1) mixed integer nonlinear programming problem. Then, we obtain two PWMIP models by means of a convex combination approach [17] and with the approach proposed in [21]. The latter consists of reducing the cardinality of a subset of binary variables to a logarithmic number of binary variables. Finally, we propose a variable neighborhood search (VNS) procedure [10,11]. Our preliminary numerical results indicate that the first model is more effective and that the VNS approach allows to obtain feasible solutions in less computational cost.

关键词： Wireless OFDMA networks Downlink resource allocation mixed integer nonlinear programming Piecewise mixed integer linear programming

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A Genetic Algorithm-based Hybrid Optimization Approach for Microgrid Energy Management 5

A Genetic Algorithm-based Hybrid Optimization Approach for M...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

作者： Li, Hepeng Zang, Chuanzhi Zeng, Peng Yu, Haibin Li, Zhongwen Chinese Acad Sci Shenyang Inst Automat Lab Networked Control Syst Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781479987306

This paper proposes a novel Meta-heuristic based hybrid optimization method for Microgrid energy management system. First, microgrid energy management problem is modeled as a mixed integer nonlinear programming with the consideration of quadratic fuel cost of distributed generators and their startup/shut-down states. In order to obtain a favorable solution, a hybrid solution procedure combined quadratic programming and genetic algorithm is proposed to solve the problem. Then, the proposed method is verified via numerical simulation. Through the comparison of optimization result with IBM ILOG CPLEX Optimizer, simulation shows that the proposed algorithm has the advantage of finding better scheduling solution which leads to less operating cost.

关键词： Microgrids Energy management system mixed integer nonlinear programming Genetic algorithm Optimization

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