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Optimal replenishment policies for deteriorating items and permissible delay in payments

IMA JOURNAL OF MANAGEMENT MATHEMATICS 2017年第2期28卷 235-243页

作者： Benkherouf, Lakdere Gilding, Brian H. Kuwait Univ Coll Sci Dept Stat & Operat Res POB 5969 Safat 13060 Kuwait Kuwait Univ Coll Sci Dept Math POB 5969 Safat 13060 Kuwait

This paper examines the problem of finding an optimal replenishment policy for a single product inventory model with a finite planning horizon. Changes in inventory level are caused by deterioration of the product and a demand which varies with time, and the inventory holder is permitted to delay payment to the supplier of the product. A consequence of the latter feature is that the objective function in the resulting mixed integer non-linear programming problem does not possess the smoothness required for the straightforward application of techniques to be found in the literature to date. The authors overcome this difficulty by reducing an appropriate technique to its core mathematical essentials. It is shown that the optimization problem with a fixed number of replenishment periods has a unique global optimal solution, and that the corresponding optimal value is a strictly convex function of this number. Numerical examples are presented, and managerial implications are discussed.

关键词： inventory control deteriorating items finite horizon problem mixed integer non-linear programming optimization

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Shared and practical approach to conserve utilities in eco-industrial parks

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COMPUTERS & CHEMICAL ENGINEERING 2016年第0期93卷 221-233页

作者： Nair, Sajitha K. Guo, Yingjian Mukherjee, Ushnik Karimi, I. A. Elkamel, Ali Natl Univ Singapore Dept Chem & Biomol Engn 4 Engn Dr 4 Singapore 117585 Singapore Univ Waterloo Dept Chem Engn 200 Univ Ave West Waterloo ON N2L 3G1 Canada

Conserving utilities in an eco-industrial park (EIP) by exploiting the synergistic heating/cooling needs of its inhabitants can have significant economic and environmental benefits. However, a successful implementation of an EIP-wide heat integration involves much more than the simple minimization of utility usage. Like any collaborative endeavour involving independent and diverse profit-making enterprises, an EIP-wide heat integration faces several real and practical challenges such as exchanger locations, stream transports over long distances, etc. In this work, we propose a mixed-integer nonlinear programming model (MINLP) for configuring an EIP-wide multi-enterprise heat exchanger network (HEN). We propose a practical and rational strategy that (1) considers all the major capital and operating costs, and utility savings, (2) selects an optimum HEN location with the highest net present value, (3) uses a third party logistics provider for managing and operating the HEN, and (4) ensures an identical rate of return on investment for all participating enterprises. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： EIP Heat exchanger network synthesis Inter-plant integration mixed integer non-linear programming Optimization

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A multi-objective optimization and multi-criteria evaluation integrated framework for distributed energy system optimal planning

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ENERGY CONVERSION AND MANAGEMENT 2018年 166卷 445-462页

作者： Jing, Rui Zhu, Xingyi Zhu, Zhiyi Wang, Wei Meng, Chao Shah, Nilay Li, Ning Zhao, Yingru Xiamen Univ Coll Energy Xiamen Peoples R China CLP Power Hong Kong Ltd East & West Reg Hong Kong Hong Kong Peoples R China Imperial Coll London Dept Chem Engn London England

This study proposes an integrated framework for planning distributed energy system with addressing the multi-objective optimization and multi-criteria evaluation issues simultaneously. The framework can be decomposed into two stages. At the optimization stage, the system design and dispatch are optimized considering multiple objectives by E-constraint method. Three decision making approaches are applied to identify the Pareto optimal solution. At the evaluation stage, a combined Analytic Hierarchy Process and Gray Relation Analysis method is proposed to evaluate and rank various optimal solutions when different objectives and cases are considered. Two stages of work are integrated by introducing the baseline conditions. As an illustrative example, an optimal planning model for a solar-assisted Solid Oxide Fuel Cell distributed energy system is proposed by mixed integer non-linear programming approach firstly. Then, the system is applied to different cases considering two types of buildings located in three climate zones. The obtained optimal solutions are further evaluated by the proposed multi-criteria evaluation method. Therefore, the overall optimal system design and dispatch strategy, as well as the best demonstration site can be identified comprehensively considering multiple objectives. In general, the results have verified the effectiveness of the proposed framework.

关键词： Distributed energy system mixed integer non-linear programming Solid Oxide Fuel Cell Multi-objective optimization Decision making Multi-criteria evaluation

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OPTIMAL MANUFACTURING BATCH SIZE WITH REWORK FOR A FINITE-HORIZON AND TIME-VARYING DEMAND RATES INVENTORY MODEL

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RAIRO-OPERATIONS RESEARCH 2017年第1期51卷 173-187页

作者： Benkherouf, Lakdere Omar, Mohamed Kuwait Univ Coll Sci Dept Stat & Operat Res POB 5969 Safat 13060 Kuwait Univ Malaya Fac Sci Inst Math Sci Kuala Lumpur 50603 Malaysia

This paper proposes a finite-horizon and time-varying demand rate function formulations for the optimal manufacturing batch size model with rework. The basic model is found in [Jamal et al. Comput. Ind. Eng. 47 (2004) 77-89.]. Two policies 1 and 2 are considered. In Policy 1 defective items produced in a given period are remanufactured within the same period while Policy 2 accumulates the defective items until the last period. The search for the optimal manufacturing batch size for policies 1 and 2 is shown to reduce to the problem of determining the number of manufacturing-rework periods as well as their starting and finishing times. This leads to the examination of two mixed integer non-linear programming problem which are completely solved by appealing to some established techniques proposed in [Al-Khamis et al. Int. J. Syst. Sci. 45 (2014) 2196-2202]. Numerical results are also presented for illustration.

关键词： Inventory control finite horizon problem mixed integer non-linear programming optimization

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The Plant Layout Optimization Considering the Operating Conditions

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JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 2017年第7期50卷 568-576页

作者： Lee, Da Hye Lee, Chang Jun Pukyong Natl Univ Dept Safety Engn 365 Sinseon Ro Busan 608739 South Korea

Plant layout is one of the most important factors for reducing plant construction costs. In the research field of plant layouts, the main purpose is to minimize the total length and cost of pipelines between equipment by satisfying various constraints, such as safety regulations and passages for operators. However, previous research overlooks the consideration of operating conditions. Additionally, sufficient safety distances between equipment have to be guaranteed to mitigate danger or domino accidents, and maintenance spaces should be considered for on-site repairs or maintenance. Moreover, various multi-floor plants have been constructed. Therefore, an appropriate algorithm for handling these issues urgently needs to be developed. Equations for the mixed integer non-linear programming problem considering various issues are proposed in this study. In these equations, the objective function is the total summation of pipeline and additional energy costs generated by pressure drop and heat transfer. Additionally, predefined safety and maintenance spaces are transformed into inequality constraints. Because it is not always possible to use the derivatives of equations, such as in this study, an original particle swarm optimization technique is employed. Two case studies are illustrated to verify the efficacy of the proposed algorithm.

关键词： Plant Layout mixed integer non-linear programming Normal Operating Conditions PSO Technique

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AC load flow based model for transmission expansion planning

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ELECTRIC POWER SYSTEMS RESEARCH 2019年 171卷 26-35页

作者： Farrag, Mahmoud Ali Ali, Kareem Mohamed Omran, Shaimaa Cairo Univ Elect Power & Machines Dept Fac Engn 1 Gamaa St Cairo 12613 Egypt Natl Res Ctr Syst & Informat Dept Engn Res Div El Buhouth St Cairo 12622 Egypt

This paper proposes an accurate model to solve the transmission network expansion planning (TNEP) problem. The TNEP problem is solved using a linear DC model, a mixed integer linear DC model, and the proposed accurate exact mixed integer non-linear AC model. A 19 bus system which is a part of the 220 kV Egyptian transmission network is used for the verification of the proposed load flow models. The proposed exact nonlinear AC load flow based model that considered control of active and reactive power flow in the network and considered the power losses in the system yielded promising results when compared to DC load flow based linear and mixed integer linear models. It provided a planned network with least number of added lines and consecutively with the least cost.

关键词： Transmission network expansion planning mixed integer linear programming mixed integer non-linear programming DC load flow model AC load flow model

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Decentralized Greedy-Based Algorithm for Smart Energy Management in Plug-in Electric Vehicle Energy Distribution Systems

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IEEE ACCESS 2020年 8卷 75666-75681页

作者： Mehrabi, Abbas Nunna, H. S. V. S. Kumar Dadlani, Aresh Moon, Seungpil Kim, Kiseon Nottingham Trent Univ Dept Comp & Technol Nottingham NG11 8NS England Nazarbayev Univ Dept Elect & Comp Engn Astana 010000 Kazakhstan Korea Elect Power Res Inst KEPRI Deajeon 34056 South Korea Gwangju Inst Sci & Technol Sch Elect Engn & Comp Sci Gwangju 61005 South Korea

Variations in electricity tariffs arising due to stochastic demand loads on the power grids have stimulated research in finding optimal charging/discharging scheduling solutions for electric vehicles (EVs). Most of the current EV scheduling solutions are either centralized, which suffer from low reliability and high complexity, while existing decentralized solutions do not facilitate the efficient scheduling of on-move EVs in large-scale networks considering a smart energy distribution system. Motivated by smart cities applications, we consider in this paper the optimal scheduling of EVs in a geographically large-scale smart energy distribution system where EVs have the flexibility of charging/discharging at spatially-deployed smart charging stations (CSs) operated by individual aggregators. In such a scenario, we define the social welfare maximization problem as the total profit of both supply and demand sides in the form of a mixed integer non-linear programming (MINLP) model. Due to the intractability, we then propose an online decentralized algorithm with low complexity which utilizes effective heuristics to forward each EV to the most profitable CS in a smart manner. Results of simulations on the IEEE 37 bus distribution network verify that the proposed algorithm improves the social welfare by about 30% on average with respect to an alternative scheduling strategy under the equal participation of EVs in charging and discharging operations. Considering the best-case performance where only EV profit maximization is concerned, our solution also achieves upto 20% improvement in flatting the final electricity load. Furthermore, the results reveal the existence of an optimal number of CSs and an optimal vehicle-to-grid penetration threshold for which the overall profit can be maximized. Our findings serve as guidelines for V2G system designers in smart city scenarios to plan a cost-effective strategy for large-scale EVs distributed energy management.

关键词： Vehicle-to-grid Cascading style sheets Optimal scheduling Batteries Scheduling Electric vehicle-to-grid (V2G) distributed energy management mixed integer non-linear programming greedy-based algorithm smart cities

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Water network synthesis using mutation-enhanced particle swarm optimization

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PROCESS SAFETY AND ENVIRONMENTAL PROTECTION 2007年第B6期85卷 507-514页

作者： Hul, S. Tan, R. R. Auresenia, J. Fuchino, T. Foo, D. C. Y. De La Salle Univ Maynila Dept Chem Engn Manila Philippines Tokyo Inst Technol Meguro Ku Tokyo Japan Univ Nottingham Sch Chem & Environm Engn Nottingham NG7 2RD England

Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.

关键词： process integration water minimization mixed integer non-linear programming particle swarm optimization

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Some transformation techniques with applications in global optimization

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JOURNAL OF GLOBAL OPTIMIZATION 2009年第2-3期43卷 391-405页

作者： Lundell, Andreas Westerlund, Joakim Westerlund, Tapio Abo Akad Univ Proc Design Lab SF-20500 Turku Finland

In this paper some transformation techniques, based on power transformations, are discussed. The techniques can be applied to solve optimization problems including signomial functions to global optimality. Signomial terms can always be convexified and underestimated using power transformations on the individual variables in the terms. However, often not all variables need to be transformed. A method for minimizing the number of original variables involved in the transformations is, therefore, presented. In order to illustrate how the given method can be integrated into the transformation framework, some mixed integer optimization problems including signomial functions are finally solved to global optimality using the given techniques.

关键词： Transformation and convexification techniques Signomial functions Global optimization mixed integer non-linear programming

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Solving a two-dimensional trim-loss problem with MILP

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1998年第3期104卷 572-581页

作者： Westerlund, T Isaksson, J Harjunkoski, I Abo Akad Univ Proc Design Lab FIN-20500 Turku Finland Wisapak Corp FIN-68600 Pietarsaari Finland

In this paper a two-dimensional trim-loss problem connected to the paper-converting industry is considered. The problem is to produce a set of product paper rolls from larger raw paper rolls such that the cost for waste and the cutting time is minimized. The problem is generally non-convex due to a bilinear objective function and some bilinear constraints, which give rise to difficulties in finding efficient numerical procedures for the solution. The problem can, however, be solved as a two-step procedure, where the latter step is a mixed integer linear programming (MILP) problem. In the present formulation, both the width and length of the raw paper rolls as well as the lengths of the product paper roils are considered variables. All feasible cutting patterns are included in the problem and global optimal cutting patterns are obtained as the solution from the corresponding MILP problem. A numerical example is included to illustrate the proposed procedure. (C) 1998 Elsevier Science B.V.

关键词： optimization mixed integer non-linear programming mixed integer linear programming trim-loss problems scheduling problems

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