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International Symposium on Advanced Electrical and Communication Technologies (ISAECT)

作者： El-Harrouti, Taoufiq El Kafazi, Ismail Bannari, Rachid Amar, Sara Haddou Abouabdillah, Abdellah Ibn Tofail Univ Lab Syst Engn Ensa Kenitra Morocco

ISBN: (纸本)9781538673287

Analysis of the energy transportation cost has a wide range of scope nowadays. Satisfying the demand for minimum cost is a great challenge for the power system. The planning and modeling of the production system should put forward the objectives of greenhouse gas emission reduction and promote the deployment of renewable energy. These objectives are designed to achieve significant energy savings in the future. In this work, a mixed integer non-linear programming is used to minimize the energy transportation cost using commercial software GAMS. The obtained results show the effectiveness of the proposed method.

关键词： Optimization transportation cost mixed integer non-linear programming scheduling demand

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mixed integer quadratically-constrained programming model to solve the irregular strip packing problem with continuous rotations

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JOURNAL OF GLOBAL OPTIMIZATION 2018年第1期72卷 89-107页

作者： Cherri, Luiz H. Cherri, Adriana C. Soler, Edilaine M. Univ Sao Paulo Av Trabalhador Sao Carlense 400 BR-13566590 Sao Carlos SP Brazil Univ Estadual Paulista Av Eng Luiz Edmundo Carrijo Coube 14-01 BR-17033360 Bauru SP Brazil ODM Rua Alfredo Lopes 1717Sala E10 BR-13560460 Sao Carlos SP Brazil

The irregular strip packing problem consists of cutting a set of convex and non-convex two-dimensional polygonal pieces from a board with a fixed height and infinite length. Owing to the importance of this problem, a large number of mathematical models and solution methods have been proposed. However, only few papers consider that the pieces can be rotated at any angle in order to reduce the board length used. Furthermore, the solution methods proposed in the literature are mostly heuristic. This paper proposes a novel mixed integer quadratically-constrained programming model for the irregular strip packing problem considering continuous rotations for the pieces. In the model, the pieces are allocated on the board using a reference point and its allocation is given by the translation and rotation of the pieces. To reduce the number of symmetric solutions for the model, sets of symmetry-breaking constraints are proposed. Computational experiments were performed on the model with and without symmetry-breaking constraints, showing that symmetry elimination improves the quality of solutions found by the solution methods. Tests were performed with instances from the literature. For two instances, it was possible to compare the solutions with a previous model from the literature and show that the proposed model is able to obtain numerically accurate solutions in competitive computational times.

关键词： mixed integer non-linear programming Nesting problems Irregular pieces Continuous rotations

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Optimal operation of water distribution networks by predictive control using MINLP

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WATER SA 2003年第4期29卷 393-404页

作者： Biscos, C Mulholland, M Le Lann, MV Buckley, CA Brouckaert, CJ Univ KwaZulu Natal Sch Chem Engn Pollut Res Grp ZA-4041 Durban South Africa Lab Anal & Architecture Syst F-31077 Toulouse 4 France Inst Natl Sci Appl Dept GEI F-31077 Toulouse 4 France

This paper presents an approach for the operational optimisation of potable water distribution networks. The maximum of the use of low-cost power (e.g. overnight pumping) and the maintenance of a target chlorine concentration at final delivery points were defined as important optimisation objectives. The first objective is constrained by the maintenance of minimum emergency volumes in all reservoirs, while the second objective would include the minimisation of chlorine dosage and re-dosage requirements. The combination of dynamic elements (e.g. reservoirs) and discrete elements (pumps, valves, routing) makes this a challenging predictive control and constrained optimisation problem, which is being solved by MINLP (mixed integer non-linear programming). Initial experimental results show the performance of this algorithm and its ability to control the water distribution process.

关键词： drinking water mixed integer non-linear programming model predictive control

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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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Grain silo location-allocation problem with dwell time for optimization of food grain supply chain network

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2018年 111卷 40-69页

作者： Mogale, D. G. Kumar, Mukesh Kumar, Sri Krishna Tiwari, Manoj Kumar Indian Inst Technol Kharagpur Dept Ind & Syst Engn Kharagpur 721302 W Bengal India Univ Cambridge Inst Mfg Dept Engn Cambridge England

In the last few decades, production and procurement of food grain in India have steadily increased, however, storage capacity has not increased proportionally. The government of India (GOI) is establishing the various capacitated silos across the country to bridge this storage capacity gap. This paper presents a novel integrated multi-objective, multi-modal and multi-period mathematical model for grain silo location-allocation problem with Dwell time to support the decision-making process of GOI. Two conflicting objectives-minimization of total supply chain network cost and total lead time (transit and dwell time) are simultaneously optimized using two Pareto based multi-objective algorithms with calibrated parameters.

关键词： Facility location-allocation problem Multi-objective optimization mixed integer non-linear programming Food grain supply chain non-dominated sorting chemical reaction optimization (NCRO)

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Pattern of secure bilateral transactions ensuring power economic dispatch in hybrid electricity markets

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APPLIED ENERGY 2009年第7-8期86卷 1000-1010页

作者： Kumar, Ashwani Gao, Wenzhong Tennessee Technol Univ Dept Elect & Comp Engn Cookeville TN 38505 USA

This paper proposes a new method for secure bilateral transactions determination ensuring economic power dispatch of the generators using new AC distribution factors for pool and bilateral coordinated markets. The new optimization problem considers simultaneous minimization of deviations from scheduled transactions and fuel cost of the generators in the network. The fuel cost has been obtained for hybrid market model and impact of different percentage of bilateral demand on fuel cost, generation share, and pattern of transactions has also been determined. The impact of optimally located unified power flow controller (UPFC) on the bilateral transactions, fuel cost and generation pattern has also been studied. The results have also been obtained for pool market model. The proposed technique has been applied on IEEE 24-bus reliability test system (RTS). (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Secure transaction matrix Transaction matrix pattern mixed integer non-linear programming UPFC location AC distribution factors

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A general purpose exact solution method for mixed integer concave minimization problems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第3期309卷 977-992页

作者： Sinha, Ankur Das, Arka Anand, Guneshwar Jayaswal, Sachin Indian Inst Management Ahmedabad Prod & Quantitat Methods Ahmadabad 380015 Gujarat India Indian Inst Management Visakhapatnam Prod & Operat Management Visakhapatnam 530003 Andhra Pradesh India

In this article, we discuss an exact algorithm for solving mixed integer concave minimization problems. A piecewise inner-approximation of the concave function is achieved using an auxiliary linear program that leads to a bilevel program, which provides a lower bound to the original problem. The bilevel program is reduced to a single level formulation with the help of Karush-Kuhn-Tucker (KKT) conditions. Incorporating the KKT conditions lead to complementary slackness conditions that are linearized using BigM, for which we identify a tight value for general problems. Multiple bilevel programs, when solved over iterations, guarantee convergence to the exact optimum of the original problem. Though the algorithm is general and can be applied to any optimization problem with concave function(s), in this paper, we solve two common classes of operations and supply chain problems;namely, the concave knapsack problem, and the concave production-transportation problem. The computational experiments indicate that our proposed approach outperforms the customized methods that have been used in the literature to solve the two classes of problems by an order of magnitude in most of the test cases.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Global optimization Concave minimization mixed integer non-linear programming Knapsack problem Production -transportation problem

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Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

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APPLIED ENERGY 2016年 164卷 590-606页

作者： Nosratabadi, Seyyed Mostafa Hooshmand, Rahmat-Allah Gholipour, Eskandar Univ Isfahan Dept Elect Engn Fac Engn Esfahan Iran

One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a mixed integer non-linear programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Virtual power plant Stochastic scheduling Industrial microgrid Demand response load mixed integer non-linear programming

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Probabilistic approach for optimal allocation of wind-based distributed generation in distribution systems

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IET RENEWABLE POWER GENERATION 2011年第1期5卷 79-88页

作者： Atwa, Y. M. El-Saadany, E. F. Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Recent development in small renewable/clean generation technologies such as wind turbines, photovoltaic, fuel cells, microturbines and so on has drawn distribution utilities' attention to possible changes in the distribution system infrastructure and policy by deploying distributed generation (DG) in distribution systems. In this study, a methodology has been proposed for optimally allocating wind-based DG units in the distribution system so as to minimise annual energy loss. The methodology is based on generating a probabilistic generation-load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer non-linear programming (MINLP), with an objective function for the system's annual energy losses minimise. The constraints include voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units. This proposed technique is applied to a typical rural distribution system and compared to the traditional planning technique (constant output power of DG units and constant peak load profile).

关键词： power generation planning distribution systems Optimisation techniques wind power plants nonlinear programming Distribution networks Power system planning and layout Wind power plants wind turbines probability MINLP wind-based distributed generation optimal allocation mixed integer non-linear programming integer programming distributed power generation probabilistic generation-load model deterministic planning problem Other topics in statistics

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