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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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An efficient search algorithm for obtaining the optimal replenishment strategies in assembly-type just-in-time supply chain systems

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2018年第2期35卷 118-128页

作者： Yao, Ming-Jong Hsu, Tien-Cheng Natl Chiao Tung Univ Dept Transportat & Logist Management Hsinchu Taiwan Changhua Christian Hosp Informat Syst Dept Changhua Taiwan

An assembly-type just-in-time (JIT) supply chain system is composed of a main serial supply chain and several branching serial supply chains merging to the main supply chain. Under the assumption of constant demand rate, the replenishment problem in the assembly-type JIT supply chain systems can be formulated as a mixed-integer non-linear programming problem. We conduct thorough theoretical analysis on the properties of the objective function value curve in this study. Following our theoretical analysis, we propose a search algorithm that effectively solves an optimal solution. Our numerical experiments show that the average run time of the proposed algorithm grows in a linear order of the problem size, and the proposed algorithm may serve as an efficient solution approach for the decision-maker.

关键词： Kanban supply chain just-in-time mixed integer non-linear programming search algorithm

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Optimal distributed generation location using mixed integer non-linear programming in hybrid electricity markets

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IET GENERATION TRANSMISSION & DISTRIBUTION 2010年第2期4卷 281-298页

作者： Kumar, A. Gao, W. Natl Inst Technol Dept Elect Engn Kurukshetra Haryana India Tennessee Technol Univ Energy Syst Res Ctr Dept Elect & Comp Engn Cookeville TN USA

This study presents mixed integer non-linear programming (MINLP) approach for determining optimal location and number of distributed generators in hybrid electricity market. For optimal location of distributed generation (DG), first the most appropriate zone has been identified based on real power nodal price and real power loss sensitivity index as an economic and operational criterion. After identifying the suitable zone, mixed integer non-linear programming approach has been applied to locate optimal place and number of distributed generators in the obtained zone. The non-linear optimisation approach consists of minimisation of total fuel cost of conventional and DG sources as well as minimisation of line losses in the network. The pattern of nodal real and reactive power prices, line loss reduction and fuel cost saving has been obtained. The results have also been obtained for pool electricity market model for comparison. The impact of demand variation on the results has also been obtained for both the market models. The proposed MINLP-based optimisation approach has been applied for IEEE 24 bus reliability test system.

关键词： power markets power system reliability distributed generation optimal location hybrid electricity markets nonlinear programming non-linear optimisation Reliability real power loss sensitivity index real power nodal price Power system management, operation and economics power system simulation Optimisation techniques mixed integer non-linear programming IEEE 24 bus reliability test system

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Sustainable maritime inventory routing problem with time window constraints

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2017年 61卷 77-95页

作者： De, Arijit Kumar, Krishna Gunasekaran, Angappa Tiwari, Manoj Kumar Indian Inst Technol Kharagpur Dept Ind & Syst Engn Kharagpur 721302 W Bengal India Univ Massachusetts Dept Decis & Informat Sci 285 Old Westport Rd N Dartmouth MA 02748 USA

Maritime inventory routing problem is addressed in this paper to satisfy the demand at different ports during the planning horizon. It explores the possibilities of integrating slow steaming policy as mentioned in Kontovas et al. (2011) and Norstad et al. (2011) within ship routing. A mixed integer non-linear programming model is presented considering various scheduling and routing constraints, loading/unloading constraints and vessel capacity constraints. non-linear equation between fuel consumption and vessel speed has been incorporated to capture the sustainability aspects. Several time window constraints are inculcated in the mathematical model to enhance the service level at each port. Penalty costs are incurred if the ship arrives early before the starting of the time window or if it finishes its operation after the ending of the time window. Costs associated with the violation of time window helps in maintaining a proper port discipline. Now, owing to the inherent complexity of the aforementioned problem, an effective search heuristics named Particle Swarm Optimization for Composite Particle (PSO-CP) is employed. Particle Swann Optimization Differential Evolution (PSO-DE), Basic PSO and Genetic Algorithm (GA) are used to validate the result obtained from PSO-CP. Computational results provided for different problem instances shows the superiority of PSO-CP over the other algorithms in terms of the solution obtained.

关键词： Ship routing and scheduling Maritime transportation mixed integer non-linear programming Maritime inventory routing Slow steaming Fuel consumption Particle swarm optimization for composite particle

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Bulk wheat transportation and storage problem of public distribution system

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 104卷 80-97页

作者： Mogale, D. G. Kumar, Sri Krishna Garcia Marquez, Fausto Pedro Tiwari, Manoj Kumar Indian Inst Technol Dept Ind & Syst Engn Kharagpur 721302 W Bengal India Univ Castilla La Mancha Ingenium Res Grp Ciudad Real Spain

This research investigates the multi-period multi-modal bulk wheat transportation and storage problem in a two-stage supply chain network of Public Distribution System (PDS). The bulk transportation and storage can significantly curtail the transit and storage losses of food grains, which leads to substantial cost savings. A mixed integer non-linear programming model (MINLP) is developed after studying the Indian wheat supply chain scenario, where the objective is to minimize the transportation, storage and operational cost of the food grain incurred for efficient transfer of wheat from producing states to consuming states. The cost minimization of Indian food grain supply chain is a very complex and challenging problem because of the involvement of the many entities and their constraints such as seasonal procurement, limited scientific storages, varying demand, mode of transportation and vehicle capacity constraints. To address this complex and challenging problem of food grain supply chain, we have proposed the novel variant of Chemical Reaction Optimization (CRO) algorithm which combines the features of CRO and Tabu search (TS) and named it as a hybrid CROTS algorithm (Chemical reaction optimization combined with Tabu Search). The numerous problems with different sizes are solved using the proposed algorithm and obtained results have been compared with CRO. The comparative study reveals that the proposed CROTS algorithm offers a better solution in less computational time than CRO algorithm and the dominance of CROTS algorithm over the CRO algorithm is demonstrated through statistical analysis. (C) 2016 Published by Elsevier Ltd.

关键词： Transportation-storage problem Food grain supply chain Public distribution system mixed integer non-linear programming Chemical reaction optimization

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Joint Video Packet Scheduling, Subchannel Assignment and Power Allocation for Cognitive Heterogeneous Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2017年第3期16卷 1703-1712页

作者： Xu, Lei Nallanathan, Arumugam Song, Xiaoqin Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China Kings Coll London Dept Informat London WC2R 2LS England Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210096 Jiangsu Peoples R China

In this paper, a joint video scheduling, subchannel assignment, and power allocation problem in cognitive heterogeneous networks are modeled as a mixed integer non-linear programming (MINLP), which maximizes the minimum video transmission quality among different secondary mobile terminals (MTs) subject to the total available energy at each secondary, the total interference power at each primary base station, the total available capacity at each radio interface of each secondary MTs, and the video sequence encoding characteristic. In order to solve it, we decompose the original MINLP as joint subchannel and power allocation problem and video packet scheduling problem. Then, we model the joint subchannel and power allocation problem as a max-min fractional programming, and transform it as a convex optimization problem. Finally, we utilize dual decomposition method to design a joint subchannel and power allocation algorithm, and propose a video packet scheduling scheme based on auction theory to maximize the video quality for each secondary MT. Simulation results demonstrate that the proposed framework not only improves the video transmission quality significantly, but also guarantees the fairness among different secondary MTs.

关键词： Cognitive heterogeneous networks packet scheduling video traffic auction theory mixed integer non-linear programming

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Modeling and forecasting energy flow between national power grid and a solar-wind-pumped-hydroelectricity (PV-WT-PSH) energy source

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ENERGY CONVERSION AND MANAGEMENT 2017年 136卷 382-394页

作者： Jurasz, Jakub AGH Univ Sci & Technol Fac Management Dept Engn Management Krakow Poland

The structure of modern energy systems has evolved based on the assumption that it is the demand side which is variable, whilst the supply side must adjust to forecasted (or unforecasted) changes. But the increasing role of variable renewable energy sources (VRES) has led to a situation in which the supply side is also becoming more and more unpredictable. To date, various approaches have been proposed to overcome this impediment. This paper aims to combine mixed integer modeling with an Artificial Neural Networks (ANN) forecasting method in order to predict the volume of energy flow between a local balancing area which is using PV-WT-PSH and the national power system (NPS). Calculations has been performed based on the hourly time series of wind speed, irradiation and energy demand. The results indicate that both probabilistic and ANN models generate comparably accurate forecasts;however, the opportunity for improvement in the former appears to be significantly greater. The mean prediction error (for a one hour ahead forecasts) for the best model was 0.15 MW h, which amounts to less than 0.2% of a mean hourly energy demand of the considered energy consumer. The proposed approach has huge potential to reduce the impact of VRES on the NPS operation as well as can be used to facilitate the process of their integration and increase their share in covering energy demand. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： non-dispatchable energy sources Artificial neural networks RES integration mixed integer non-linear programming

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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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Optimal replenishment policies for deteriorating items and permissible delay in payments

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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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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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