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Synthesis of reverse osmosis desalination network under boron specifications

DESALINATION 2015年 371卷 26-36页

作者： Saif, Y. Almansoori, A. Petr Inst Dept Chem Engn Abu Dhabi U Arab Emirates

Recent regulations regarding water quality motivated research in reverse osmosis (RO) technology for water desalination especially under boron restrictions. Boron control in the permeate products by reverse osmosis technology comprises several mitigation options which impose capital and operation costs. In our study, we investigate the design of RO system under the design concept of split partial second pass reverse osmosis (SPSPRO) in order to allow extraction of permeate streams along the RO pressure vessels. The design approach is based on superstructure optimization which allows the identification of optimal process layout and optimal operation conditions of the process units. pH adjustment of the network streams is also included in the model to control boron species distribution during the separation process. A mixed integer nonlinear program (MINLP) model is subsequently formulated based on the superstructure representation. The mathematical programming formulation is demonstrated on a case study to show the application of the mathematical programming model. The results show lower treatment cost through the proposed mathematical programming model. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Boron Seawater desalination Reverse osmosis network mixed integer nonlinear programming

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Optimal scheduling of household appliances for demand response

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ELECTRIC POWER SYSTEMS RESEARCH 2014年第Nov.期116卷 24-28页

作者： Setlhaolo, Ditiro Xia, Xiaohua Zhang, Jiangfeng Univ Pretoria Dept Elect Elect & Comp Engn Ctr New Energy Syst ZA-0002 Pretoria South Africa Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XQ Lanark Scotland

In this paper, residential demand response is studied through the scheduling of typical home appliances in order to minimize electricity cost and earn the relevant incentive. A mixed integer nonlinear optimization model is built under a time-of-use electricity tariff. A case study shows that a household is able to shift consumption in response to the varying prices and incentives, through which the consumer may realize an electricity cost saving of more than 25%. It has also been shown that at different values of the weighting factor a gives varying costs, from which the consumer is able to choose according to their preferences. Therefore a final decision about participation in the program could be made. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Household energy management Household appliances Scheduling Demand response Inconvenience mixed integer nonlinear programming

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Global Transformer Optimization Method Using Evolutionary Design and Numerical Field Computation

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IEEE TRANSACTIONS ON MAGNETICS 2009年第3期45卷 1720-1723页

作者： Amoiralis, Eleftherios I. Georgilakis, Pavlos S. Tsili, Marina A. Kladas, Antonios G. Tech Univ Crete Dept Prod Engn & Management Iraklion 73100 Greece Natl Tech Univ Athens Fac Elect & Comp Engn Athens 15780 Greece

This paper addresses the complex optimum transformer design problem, which is formulated as a mixed-integer nonlinear programming problem, by introducing an integrated design optimization method based on evolutionary algorithms and numerical electromagnetic and thermal field computations. The main contributions of this research are: i) introduction of a new overall transformer optimization method, minimizing either the overall transformer materials cost or the overall transformer materials and operating cost, ii) expansion of the solution space by innovative techniques that define the variation of crucial design variables such as the conductors' cross-section, ensuring global optimum transformer designs, and iii) incorporation of numerical field computation in order to validate the feasibility of the optimum designs. The proposed method is compared with a heuristic optimization method of the transformer manufacturing industry and the results demonstrate the robustness and the superiority of this new approach.

关键词： Design method finite element method (FEM) mixed integer nonlinear programming optimization methods transformer

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Technical and economic analysis of home energy management system incorporating small-scale wind turbine and battery energy storage system

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JOURNAL OF CLEANER PRODUCTION 2017年 159卷 106-118页

作者： Hemmati, Reza Kermanshah Univ Technol Dept Elect Engn Kermanshah Iran

Home energy management system (HEMS) is an important problem that has been attracting significant attentions in the recent years. However, the conventional HEMS includes several shortcomings. The conventional HEMSs mainly utilize battery energy storage system (BESS) to deal with energy uncertainties. But they only ascertain optimal charging-discharging pattern for BESS and the power and capacity of BESS are not optimally determined. Furthermore, most of the HEMSs are modeled as a mixed integer linear programming (MILP) including linearization and relaxations. Additionally, considering all possible operating conditions for home has not been adequately addressed in the existing HEMSs. The possible operating conditions are (i) receiving energy from the main grid (i.e., purchasing energy), (ii) sending energy to the utility grid (i.e., selling energy), (iii) working on standalone mode as disconnected from the network (i.e., net-zero energy building). As a result, current paper deals with these existing challenges at the same time. This paper presents HEMS including small-scale wind turbine, BESS, load curtailment option, and fuel cell vehicle. The introduced HEMS not only determines optimal charging discharging pattern for BESS, but also specifies optimal capacity and optimal rated power of the BESS at the same time. The proposed HEMS is expressed as a mixed integer nonlinear programming (MINLP) and solved by cultural algorithm as an effective Meta-heuristic optimization algorithm. All three operating conditions are considered for home. Output power of wind unit is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to deal with uncertainties. Results emphasize on the feasibility and usefulness of the introduced HEMS. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Battery energy storage system Home energy management system Stochastic optimization mixed integer nonlinear programming Wind turbine

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Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

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APPLIED SOFT COMPUTING 2020年 86卷

作者： Ghasemishabankareh, Behrooz Li, Xiaodong Ozlen, Melih Neumann, Frank RMIT Univ Sch Sci Melbourne Vic Australia Univ Adelaide Sch Comp Sci Adelaide SA Australia

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Minimum cost flow problem Genetic algorithm Representation scheme mixed integer nonlinear programming Taguchi experimental design

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Optimal models for a multi-stage supply chain system controlled by kanban under just-in-time philosophy

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第1期172卷 179-200页

作者： Wang, SJ Sarker, BR Louisiana State Univ Dept Ind Engn Baton Rouge LA 70803 USA SE Missouri State Univ Dept Ind & Engn Technol Cape Girardeau MO 63701 USA

This research studies a multi-stage supply chain system that operates under a JIT (just-in-time) delivery policy. Kanbans play an important role in the information and material flows in a supply chain system. Thus, a kanban mechanism is employed to assist in linking different production processes in a supply chain system to implement the scope of JIT philosophy. For a multi-stage supply chain system, a mixed-integer nonlinear programming (MINLP) problem is formulated from the perspective of JIT delivery policy where a kanban may reflect to a transporter such as a truck or a fork-lifter. The number of kanbans, the batch size, the number of batches and the total quantity over one period are determined optimally. It is solved optimally by branch and bound method. A greedy heuristic to avoid the large computational time in branch-and-bound algorithm is developed for solving a large MINLP. Coupled with plant-wide efforts for cost control and management commitment, a logistic system for controlling the production as well as the supply chain is built, which results in minimizing the total cost of the supply chain system. The results show that the improvements in reduction of inventory, wasted labor and customer service in a supply chain are significantly accomplished through the kanban mechanism. (C) 2004 Elsevier B.V. All rights reserved.

关键词： kanban supply chain inventory control mixed integer nonlinear programming

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A planar single facility location and border crossing problem

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COMPUTERS & OPERATIONS RESEARCH 2012年第12期39卷 3156-3165页

作者： Canbolat, Mustafa S. Wesolowsky, George O. SUNY Coll Brockport Brockport NY 14420 USA McMaster Univ DeGroote Sch Business Hamilton ON L8S 4L8 Canada

In this study, we tackle the problem of locating a facility in a region where a fixed line barrier divides the region into two. The resulting subregions communicate with each other through a number of passage points located on the line barrier. Our contribution is threefold. First, we formulate the problem as a mixed integer nonlinear programming (MINLP) model and provide an optimal solution methodology based on an Outer Approximation (OA) algorithm. Second, we discuss the minimax version of this problem for locating an emergency facility and use the OA algorithm to solve the problem. We then provide simple example problems and extensive computational results for both problems. Finally, we propose a one-infinity approximation approach for the latter problem which yields a linear model. Practical uses of the models have been discussed in the border crossing context. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Planar facility location Barriers to travel Passage points Border crossing Optimization mixed integer nonlinear programming Outer approximation

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Modeling without categorical variables: a mixed-integer nonlinear program for the optimization of thermal insulation systems

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OPTIMIZATION AND ENGINEERING 2010年第2期11卷 185-212页

作者： Abhishek, Kumar Leyffer, Sven Linderoth, Jeffrey T. Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA United Airlines Enterprise Optimizat Elk Grove Village IL 60007 USA Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA

Optimal design applications are often modeled by using categorical variables to express discrete design decisions, such as material types. A disadvantage of using categorical variables is the lack of continuous relaxations, which precludes the use of modern integer programming techniques. We show how to express categorical variables with standard integer modeling techniques, and we illustrate this approach on a load-bearing thermal insulation system. The system consists of a number of insulators of different materials and intercepts that minimize the heat flow from a hot surface to a cold surface. Our new model allows us to employ black-box modeling languages and solvers and illustrates the interplay between integer and nonlinear modeling techniques. We present numerical experience that illustrates the advantage of the standard integer model.

关键词： mixed integer nonlinear programming Modeling with binary variables Thermal insulation systems Categorical variables

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Simultaneously scheduling multiple turns for steel color-coating production

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2009年第3期198卷 715-725页

作者： Tang, Lixin Wang, Xianpeng Northeastern Univ Logist Inst Coll Informat Sci & Engn Shenyang 110004 Peoples R China

This paper investigates a large-scale scheduling problem in the iron and steel industry, called color-coating production scheduling (CCPS). The problem is to generate multiple production turns for the galvanized coils that dynamically arrive from upstream lines within a given scheduling horizon, and at the same time determine the sequence of these turns so that the productivity and product quality are maximized while the production cost and the number of generated turns are minimized. We formulate this problem as a mixed integer nonlinear program and propose a tabu search heuristic to obtain satisfactory solutions. Results on real production instances show that the presented model and heuristic are more effective and efficient with comparison to manual scheduling. A practical scheduling system for CCPS combining the model and heuristic has been developed and successfully implemented in a major iron and steel enterprise in China. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Color-coating production scheduling mixed integer nonlinear programming Tabu search

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Retrospective on optimization

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COMPUTERS & CHEMICAL ENGINEERING 2004年第8期28卷 1169-1192页

作者： Biegler, LT Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

In this paper, we provide a general classification of mathematical optimization problems, followed by a matrix of applications that shows the areas in which these problems have been typically applied in process systems engineering. We then provide a review of solution methods of the major types of optimization problems for continuous and discrete variable optimization, particularly nonlinear and mixed-integer nonlinear programming (MINLP). We also review their extensions to dynamic optimization and optimization under uncertainty. While these areas are still subject to significant research efforts, the emphasis in this paper is on major developments that have taken place over the last 25 years. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： process optimization nonlinear programming mixed integer nonlinear programming linear programming dynamic optimization stochastic optimization

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