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A feasibility study for the locations of waste transfer stations in urban centers: a case study on the city of Nashik, India

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JOURNAL OF CLEANER PRODUCTION 2016年 126卷 191-205页

作者： Yadav, Vinay Karmakar, Subhankar Dikshit, A. K. Vanjari, Shivkumar Indian Inst Technol Ctr Environm Sci & Engn Bombay 400076 Maharashtra India Indian Inst Technol Inter Disciplinary Program Climate Change Bombay 400076 Maharashtra India Indian Inst Technol Ctr Urban Sci & Engn Bombay 400076 Maharashtra India Nashik Municipal Corp Nasik 422002 India

Rapid population growth and high rate of urbanization make municipal solid waste management a challenging task for municipalities due to the inadequacy of infrastructural services. Taking this into consideration, this paper proposes an approach for finding economically optimal locations and feasibility demonstration of a municipal solid waste management infrastructure unit, i.e. waste transfer stations. This analytical approach consists of two basic elements: (i) a mathematical model to optimize overall cost for municipal solid waste management;and (ii) geographical information system tools to create a data inventory for the mathematical model. The novelty of the proposed model includes heterogeneity in data compilation, on-road measurements of distances and strategic allocation of transfer stations. Also, to assess waste load estimation more precisely, analyzing the impacts of heterogeneity in data and on road distances on model, three distinct cases have been considered. Further, the developed approach has been demonstrated on the city of Nashik, India. The mathematical model for Nashik city is written in a mathematical programming language AMPL and the solutions have been obtained using KNITRO solver. Optimization model selects three best locations out of eight potential locations with the optimum capacity of 200 TPD. Furthermore, the assessment of model's behavior under uncertainty has been performed with a comprehensive sensitivity analysis for further improvements. The integrity of all components in this study produces a generic framework for helping municipal officials and researchers for development of a municipal solid waste management system with transfer stations in an economically optimal manner. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Environmentally sound technologies Facility location problem mixed integer nonlinear programming Municipal solid waste management Transfer stations TSS model

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Optimal design of multiproduct batch chemical plant using NSGA-II

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ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING 2006年第1-2期1卷 13-20页

作者： Sarkar, Debasis Modak, Jayant M. Indian Inst Sci Dept Chem Engn Bangalore 560012 Karnataka India

The optimal design of a multiproduct batch chemical plant is formulated as a multiobjective optimization problem, and the resulting constrained mixed-integer nonlinear program (MINLP) is solved by the nondominated sorting genetic algorithm approach (NSGA-II). By putting bounds on the objective function values, the constrained MINLP problem can be solved efficiently by NSGA-II to generate a set of feasible nondominated solutions in the range desired by the decision-maker in a single run of the algorithm. The evolution of the entire set of nondominated solutions helps the decision-maker to make a better choice of the appropriate design from among several alternatives. The large set of solutions also provides a rich source of excellent initial guesses for solution of the same problem by alternative approaches to achieve any specific target for the objective functions. (C) 2006 Curtin University of Technology and John Wiley & Sons, Ltd.

关键词： mixed integer nonlinear programming nondominated sorting genetic algorithm multiobjective optimization batch plant design

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Linearization of Euclidean norm dependent inequalities applied to multibeam satellites design

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2019年第2期73卷 679-705页

作者： Camino, Jean-Thomas Artigues, Christian Houssin, Laurent Mourgues, Stephane Univ Toulouse CNRS UPS LAAS Toulouse France Airbus Def & Space Space Syst Telecommun Syst Dept Toulouse France

Euclidean norm computations over continuous variables appear naturally in the constraints or in the objective of many problems in the optimization literature, possibly defining non-convex feasible regions or cost functions. When some other variables have discrete domains, it positions the problem in the challenging mixed integer nonlinear programming (MINLP) class. For any MINLP where the nonlinearity is only present in the form of inequality constraints involving the Euclidean norm, we propose in this article an efficient methodology for linearizing the optimization problem at the cost of entirely controllable approximations even for non convex constraints. They make it possible to rely fully on mixed integer Linear programming and all its strengths. We first empirically compare this linearization approach with a previously proposed linearization approach of the literature on the continuous k-center problem. This methodology is then successfully applied to a critical problem in the telecommunication satellite industry: the optimization of the beam layouts in multibeam satellite systems. We provide a proof of the NP-hardness of this very problem along with experiments on a realistic reference scenario.

关键词： mixed integer Linear programming mixed integer nonlinear programming Euclidean norm linearization k-center problem Multibeam satellites

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Heuristics for convex mixed integer nonlinear programs

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2012年第2期51卷 729-747页

作者： Bonami, Pierre Goncalves, Joao P. M. IBM Corp Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA Aix Marseille Univ CNRS Lab Informat Fondamentale Marseille Marseille France

In this paper, we describe the implementation of some heuristics for convex mixed integer nonlinear programs. The work focuses on three families of heuristics that have been successfully used for mixed integer linear programs: diving heuristics, the Feasibility Pump, and Relaxation Induced Neighborhood Search (RINS). We show how these heuristics can be adapted in the context of mixed integer nonlinear programming. We present results from computational experiments on a set of instances that show how the heuristics implemented help finding feasible solutions faster than the traditional branch-and-bound algorithm and how they help in reducing the total solution time of the branch-and-bound algorithm.

关键词： mixed integer nonlinear programming Heuristics

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Compiler techniques for the distribution of data and computation

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2003年第6期14卷 545-562页

作者： Navarro, A Zapata, E Padua, D Univ Malaga Dept Comp Architecture Malaga 29080 Spain Univ Illinois Dept Comp Sci Digital Comp Lab 3318 Urbana IL 61801 USA

This paper presents a new method that can be applied by a parallelizing compiler to find, without user intervention, the iteration and data decompositions that minimize communication and load imbalance overheads in parallel programs targeted at NUMA architectures. One of the key ingredients in our approach is the representation of locality as a Locality-Communication Graph (LCG) and the formulation of the compiler technique as a mixed integer nonlinear programming (MINLP) optimization problem on this graph. The objective function and constraints of the optimization problem model communication costs and load imbalance. The solution to this optimization problem is a decomposition that minimizes the parallel execution overhead. This paper summarizes the process of how the compiler extracts the locality information from a nonannotated code and focuses on how this compiler can derive the optimization problem, solve it, and generate the parallel code with the automatically selected iteration and data distributions. In addition, we include a discussion about our model and the solutions-the decompositions-that it provides. The approach presented in the paper is evaluated using several benchmarks. The experimental results demonstrate that the MINLP formulation does not increase compilation time significantly and that our framework generates very efficient iteration/data distributions for a variety of NUMA machines.

关键词： parallelizing compiler locality analysis load balancing communication pattern mixed integer nonlinear programming

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On the exact separation of cover inequalities of maximum-depth

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OPTIMIZATION LETTERS 2022年第2期16卷 449-469页

作者： Catanzaro, Daniele Coniglio, Stefano Furini, Fabio Catholic Univ Louvain Ctr Operat Res & Econometr CORE Louvain La Neuve Belgium Univ Southampton Dept Math Sci Southampton Hants England Consiglio Nazl Ric IASI CNR Ist Anal Sistemi Informat Antonio Ruberti Rome Italy

We investigate the problem of separating cover inequalities of maximum-depth exactly. We propose a pseudopolynomial-time dynamic-programming algorithm for its solution, thanks to which we show that this problem is weakly NP-hard (similarly to the problem of separating cover inequalities of maximum violation). We carry out extensive computational experiments on instances of the knapsack and the multi-dimensional knapsack problems with and without conflict constraints. The results show that, with a cutting-plane generation method based on the maximum-depth criterion, we can optimize over the cover-inequality closure by generating a number of cuts smaller than when adopting the standard maximum-violation criterion. We also introduce the Point-to-Hyperplane Distance Knapsack Problem (PHD-KP), a problem closely related to the separation problem for maximum-depth cover inequalities, and show how the proposed dynamic programming algorithm can be adapted for effectively solving the PHD-KP as well.

关键词： Knapsack problem Cover inequalities Dynamic programming mixed integer nonlinear programming Cutting plane generation

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Centralized Self-Healing Scheme for Electrical Distribution Systems

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IEEE TRANSACTIONS ON SMART GRID 2016年第1期7卷 145-155页

作者： Cavalcante, Patricia L. Lopez, Juan Camilo Franco, John F. Rider, Marcos J. Garcia, Ariovaldo V. Malveira, Marcos R. R. Martins, Luana L. Direito, Luiz Carlos M. Ctr Pesquisa & Desenvolvimento Telecomunicacoes BR-13086902 Campinas Brazil Univ Estadual Campinas Dept Syst & Energy BR-13083852 Campinas Brazil Univ Estadual Paulista Fac Engn Ilha Solteira Dept Engn Eletr BR-15385000 Ilha Solteira Brazil AV Garcia Tecnol Informacao BR-13085415 Campinas Brazil Light Serv Eletricidade BR-33269122 Rio De Janeiro Brazil

In this paper, a two-stage procedure is proposed in order to solve the centralized self-healing scheme for electrical distribution systems. The considered self-healing actions are the reconfiguration of the distribution grid and, if needed, node and zone load-shedding. Thus, the proposed procedure determines the status of the switching devices in order to effectively isolate a faulty zone and minimize the number of de-energized nodes and zones, while ensuring that the operative and electrical constraints of the system are not violated. The proposed method is comprised of two stages. The first stage solves a mixed integer linear programming (MILP) problem in order to obtain the binary decision variables for the self-healing scheme (i.e., the switching device status and energized zones). In the second stage, a nonlinear programming (NLP) problem is solved in order to adjust the steady-state operating point of the topology found in the first stage (i.e., correction of the continuous electrical variables and load-shedding optimization). Commercial optimization solvers are used in the first stage to solve the MILP problem and in the second stage to solve the NLP problem. A 44-node test system and a real Brazilian distribution system with 964-nodes were used to test and verify the proposed methodology.

关键词： Centralized self-healing scheme load-shedding mixed integer nonlinear programming service restoration

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Heuristic approaches for support vector machines with the ramp loss

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OPTIMIZATION LETTERS 2014年第3期8卷 1125-1135页

作者： Carrizosa, Emilio Nogales-Gomez, Amaya Morales, Dolores Romero Univ Seville Fac Matemat Dept Estadist & Invest Operat Seville Spain Univ Oxford Said Business Sch Oxford England

Recently, Support Vector Machines with the ramp loss (RLM) have attracted attention from the computational point of view. In this technical note, we propose two heuristics, the first one based on solving the continuous relaxation of a mixed integer nonlinear formulation of the RLM and the second one based on the training of an SVM classifier on a reduced dataset identified by an integer linear problem. Our computational results illustrate the ability of our heuristics to handle datasets of much larger size than those previously addressed in the literature.

关键词： Support vector machines Ramp loss mixed integer nonlinear programming Heuristics

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Groundwater Pollution Sources Identification Based on Hybrid Homotopy-Genetic Algorithm and Simulation Optimization

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ENVIRONMENTAL ENGINEERING SCIENCE 2021年第8期38卷 777-788页

作者： Li, Jiuhui Lu, Wenxi Fan, Yue Jilin Univ Key Lab Groundwater Resources & Environm Minist Educ 2519 Xiefang RdPhys Chem Bldg Changchun 130012 Peoples R China Jilin Univ Jilin Prov Key Lab Water Resources & Environm Changchun Peoples R China Jilin Univ Coll New Energy & Environm Changchun Peoples R China

Genetic algorithm (GA) is often used to solve the optimization model of groundwater pollution source identification. However, GA is prone to premature convergence and fall into local optimum. Thus, homotopy algorithm and GA are used in combination to improve the disadvantage. Then hybrid homotopy-genetic algorithm (HGA) was applied to solve the optimization model. A 0-1 mixed integer nonlinear optimization model (0-1MINLP) based on kriging surrogate model was used to simultaneously identify hydraulic conductivity, location, and release history of pollution sources. The results showed that the 0-1MINLP based on a kriging surrogate model could simultaneously identify the hydraulic conductivity and information of pollution sources, while maintaining a certain level of precision and reducing calculation load. The combination of homotopy algorithm and GA can improve the shortcomings of GA that is easy to fall into premature convergence. The identification results obtained by the HGA were closer to the true values of the pollution source characteristics compared with GA.

关键词： groundwater pollution hybrid homotopy-genetic algorithm mixed integer nonlinear programming surrogate model

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Iterative Energy-Efficient Stable Matching Approach for Context-Aware Resource Allocation in D2D Communications

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IEEE ACCESS 2016年 4卷 6181-6196页

作者： Zhou, Zhenyu Ma, Guifang Dong, Mianxiong Ota, Kaoru Xu, Chen Jia, Yunjian North China Elect Power Univ Sch Elect & Elect Engn State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China Muroran Inst Technol Dept Informat & Elect Engn Muroran Hokkaido 0508585 Japan Chongqing Univ Coll Commun Engn Chongqing 400044 Peoples R China

Energy efficiency (EE) is critical to fully achieve the huge potentials of device-to-device (D2D) communications with limited battery capacity. In this paper, we consider the two-stage EE optimization problem, which consists of a joint spectrum and power allocation problem in the first stage, and a context aware D2D peer selection problem in the second stage. We provide a general tractable framework for solving the combinatorial problem, which is NP-hard due to the binary and continuous optimization variables. In each stage, user equipments (UEs) from two finite and disjoint sets are matched in a two-sided stable way based on the mutual preferences. First, the preferences of UEs are defined as the maximum achievable EE. An iterative power allocation algorithm is proposed to optimize EE under a specific match, which is developed by exploiting nonlinear fractional programming and Lagrange dual decomposition. Second, we propose an iterative matching algorithm, which first produces a stable match based on the fixed preferences, and then dynamically updates the preferences according to the latest matching results in each iteration. Finally, the properties of the proposed algorithm, including stability, optimality, complexity, and scalability, are analyzed in detail. Numerical results validate the efficiency and superiority of the proposed algorithm under various simulation scenarios.

关键词： Energy-efficient context-aware resource allocation many-to-one stable matching D2D communications iterative power allocation mixed integer nonlinear programming

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