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A system optimization method for mitigating three-phase imbalance in distribution network

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 113卷 618-633页

作者： Zeng, X. J. Zhai, H. F. Wang, M. X. Yang, M. Wang, M. Q. Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China Elect Power Res Inst China Southern Power Grid Guangzhou 510663 Guangdong Peoples R China

Three-phase imbalance is a common phenomenon in three-phase four-wire distribution network systems (DNSs), which may cause power quality deterioration, increase power losses, and can even damage appliances as well. The situation is becoming even worse because of the increasing integration of the distributed generations (DGs) and storage-capable loads into DNSs. In this paper, a joint optimization model based on the Y-connected and Delta-connected static reactive power compensation devices are proposed to mitigate the three-phase imbalance and minimize the active power losses in DNSs. The model is formulated to optimize the operation of all the devices in order to mitigate the imbalance of the whole DNS rather than a single feeder or a particular area. Meanwhile, the current imbalance of the transformer and the voltage imbalance of all three-phase nodes are simultaneously considered in the model according to the practical requirements. Several linearization techniques are applied to simplify the computation and accelerate the solving speed. These techniques convert the non-linear and non-convex model into a mixed-integer linear programming model, which can be effectively solved by off-the-shelf solvers. The effectiveness and scalability of the proposed method are verified by the test results obtained from the modified IEEE 34 and IEEE 123 test systems.

关键词： Three-phase imbalance Three-phase four-wire Joint optimization model linearization techniques mixed-integer linear programming

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Two continuous-time assignment-based models for the multi-mode resource-constrained project scheduling problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 129卷 346-353页

作者： Gnaegi, Mario Rihm, Tom Zimmermann, Adrian Trautmann, Norbert Univ Bern Dept Business Adm Schuetzenmattstr 14 CH-3012 Bern Switzerland

In the multi-mode resource-constrained project scheduling problem, a set of precedence-related project activities and, for each activity, a set of alternative execution modes are given. Each activity requires some time and some scarce resources during execution;these requirements depend on the selected execution mode. Sought is a project schedule, i.e, a start time and an execution mode for each activity, such that the project makespan is minimized. In the literature, besides a large variety of specific solution approaches, several mixed-integer linear programming (MILP) models have been proposed for this problem. We present two novel MILP models that are based on mode-selection, resource-assignment and sequencing variables;we enhance the performance of the models by eliminating some symmetric solutions from the search space and by adding some redundant sequencing constraints for pairs and for triples of activities that cannot be processed in parallel. In a comparison with reference models from the literature, it turned out that the advantages of the novel models are a simple structure, an enhanced flexibility, and a superior performance when the range of the activities' durations is relatively large.

关键词： Operations research mixed-integer linear programming Multi-mode resource-constrained project scheduling

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Tackling perishability in multi-level process industries

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2019年第17期57卷 5604-5623页

作者： Wei, Wenchao Amorim, Pedro Guimaraes, Luis Almada-Lobo, Bernardo Beijing Jiaotong Univ Sch Econ & Management Beijing Peoples R China Beijing Jiaotong Univ Beijing Key Lab Logist Management & Technol Beijing Peoples R China Univ Porto Fac Engn INESC TEC Rua Doutor Roberto Frias 378 P-4200465 Porto Portugal

The classical multi-level lot-sizing and scheduling problem formulations for process industries rarely address perishability issues, such as limited shelf lives of intermediate products. In some industries, ignoring this specificity may result in severe losses. In this paper, we start by extending a classical multi-level lot-sizing and scheduling problem formulation (MLGLSP) to incorporate perishability issues. We further demonstrate that with the objective of minimising the total costs (purchasing, inventory and setup), the production plans generated by classical models are often infeasible under a setting with perishable products. The model distinguishes different perishability characteristics of raw materials, intermediates and end products according to various industries. Finally, we provide quantitative insights on the importance of considering perishability for different production settings when solving integrated production planning and scheduling problems.

关键词： Multi-level production process perishability production modelling lot-sizing and scheduling mixed-integer linear programming

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Continuous-Time Locational Marginal Price of Electricity

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IEEE ACCESS 2019年 7卷 129480-129493页

作者： Khatami, Roohallah Parvania, Masood Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA

Modern electricity markets with large penetration of renewable energy resources require fair and accurate pricing methods to elicit generation flexibility and foster competition in electricity markets. This paper proposes the fundamental theory and closed-form formulas for continuous-time locational marginal price (LMP) of electricity, which more accurately integrates the spatio-temporal variations of load and operational constraints of power systems in the electricity price calculation. This paper first formulates the network-constrained generation scheduling and pricing problems as continuous-time optimal control problems using two methods for modeling transmission network, i.e., Theta and generation shift factor (GSF) methods. The continuous-time network-constrained scheduling and pricing problems minimize in their objective functional the total operation cost of power systems over the scheduling horizon subject to generation and transmission constraints. The closed-form continuous-time LMP formulas are derived for each transmission network model, which explicitly include terms that reflect the simultaneous spatio-temporal impacts of transmission flow limits and intertemporal generation ramping constraints in LMP formation. A scalable and computationally efficient function space solution method is proposed that converts the continuous-time problems into mixed integer linear programming problems with finite-dimensional decision space. The proposed solution method enables high-fidelity solution of transmission-constrained scheduling and pricing problems in higher dimensional spaces, while including as a special case the current discrete-time solutions. The proposed models are implemented on a three-bus system and the IEEE reliability test system, where the proposed models showcase more accuracy in reflecting the impacts of fast net-load variations over discrete-time counterparts.

关键词： Network-constrained scheduling and pricing locational marginal price mixed-integer linear programming continuous-time optimal control electricity market

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Energy storage allocation in wind integrated distribution networks: An MILP-Based approach

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RENEWABLE ENERGY 2019年 134卷 1042-1055页

作者： Karimi, Ali Aminifar, Farrokh Fereidunian, Alireza Lesani, Hamid Univ Tehran Sch Elect & Comp Engn Tehran Iran KN Toosi Univ Technol Elect Engn Dept Tehran Iran

Due to the unpredictable nature of wind energy and non-coincidence between wind units output power and demand peak load, wind units is deemed as an unreliable source of energy. In order to compensate for the short-term fluctuation of wind energy, deployment of energy storage (ES) units in various types have been introduced as a viable solution. This paper develops a stochastic mathematical model for the optimal allocation of ES units in active distribution networks (ADNs) in order to reduce wind power spillage and load curtailment while managing congestion and voltages deviation. Nonlinearities of the original formulation are converted to linear equivalents and the final model lies within the computationally tractable mixed-integer linear programming (MILP) fashion. The IEEE 33-bus 12.66 kV radial distribution test system is utilized to illustrate the effectiveness of the proposed methodology. It was found that the rated power and capacity of ES units are depends on wind units' location and penetration level, in such a way that ES units are allocated near wind units to absorb excessive wind energy as much as possible. Furthermore, the results indicate ES units are useful for other purposes such as voltage management issue even if the wind units are not allocated. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Active distribution networks Energy storage units Wind units mixed-integer linear programming

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A multi-criteria decision analysis to include environmental, social, and cultural issues in the sustainable aggregate production plans

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 132卷 348-360页

作者： Rasmi, Seyyed Amir Babak Kazan, Cem Turkay, Merin Koc Univ Dept Ind Engn TR-34450 Istanbul Turkey

Aggregate production planning (APP) that is an important concept of supply chain management (SCM), is one of the tools to determine production rates, inventory levels, and workforce requirements for fulfilling customer demands in a multi-period setting. Traditional APP models employ a single objective function to optimize monetary issues only. In this paper, we present a multi-objective APP model to analyze economic, social, environmental, and cultural pillars inclusively;moreover, each pillar includes several sub-pillars in the model. The resulting model includes an accurate representation of the problem with binary and continuous variables under sustainability considerations. We illustrate the effectiveness of the model in an appliance manufacturer and solve the problem using an exact solution method for multi-objective mixed-integer linear programs (MOMILP). We find a large number of the non-dominated (ND) points in the objective function space and analyze their trade-offs systematically. We show how this framework supports multiple criteria decision making process in the APP problems in the presence of sustainability considerations. Our approach provides a comprehensive analysis of the ND points of sustainable APP (SAPP) problems, and hence, the trade-offs of objective functions are insightful to the decision makers.

关键词： Supply chain management Sustainability Aggregate planning Multi-criteria decision analysis Multi-objective optimization mixed-integer linear programming

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Location model for a remanufacturing reverse logistics network based on adaptive genetic algorithm

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SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL 2019年第11期95卷 1069-1084页

作者： Yan, Rui Yan, Bo Univ Calif Los Angeles Dept Math Los Angeles CA 90024 USA South China Univ Technol Sch Econ & Commerce Guangzhou Guangdong Peoples R China

Energy saving and environmental protection are important issues of today. Concerning the environmental and social need to increase the utilization of used products, this paper introduces two remanufacturing reverse logistics (RL) network models, namely, the open-loop model and the closed-loop model. In an open-loop RL system, used products are recovered by outside firms, while in a closed-loop RL system, they are returned to their original producers. The open-loop model features a location selection with two layers. For this model, a mixed-integer linear program (MILP) is built to minimize the total costs of the open-loop RL system, including the fixed cost, the freight between nodes, the operation cost of storage and remanufacturing centers, the penalty cost of unmet or remaining demand quantity, and the government-provided subsidy given to the enterprises that protect the environment. This MILP is solved using an adaptive genetic algorithm with MATLAB simulation. For a closed-loop RL network model, a special demand function considering the relationship between new and remanufactured products is developed. Remanufacturing rate, environmental awareness, service demand elasticity, value-added services, and their impacts on total profit of the closed-loop supply chain are analyzed. The closed-loop RL network model is proved effective through the analysis of a numerical example.

关键词： Reverse logistics remanufacturing adaptive genetic algorithm mixed-integer linear programming

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Scheduling identical jobs on uniform machines with a conflict graph

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COMPUTERS & OPERATIONS RESEARCH 2019年 111卷 357-366页

作者： Mallek, Amin Bendraouche, Mohamed Boudhar, Mourad USTHB Univ RECITS Lab Fac Math BP 32 El Alia Algiers Algeria Saad Dahleb Univ Fac Sci Route Soumaa BlidaBP Blida 270 Blida Algeria

This paper addresses the problem of scheduling n identical jobs on a set of m parallel uniform machines. The jobs are subjected to conflicting constraints modelled by an undirected graph G, in which adjacent jobs are not allowed to be processed on the same machine. Minimising the maximum completion time in the schedule (makespan C-max) is known to be NP-hard. We prove that when G is restricted to complete bipartite graphs the problem remains NP-hard for arbitrary number of machines, however, if m is fixed an optimal solution can be obtained in polynomial time. To solve the general case of the problem, we propose mixed-integer linear programming (MILP) formulations alongside with lower bounds and heuristic approaches. Furthermore, computational experiments are carried out to measure the performance of the proposed methods. (C) 2019 Published by Elsevier Ltd.

关键词： Scheduling Identical jobs Incompatible jobs Uniform machines Conflict graph mixed-integer linear programming

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A Benders' decomposition algorithm with combinatorial cuts for the multi-manned assembly line balancing problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第3期278卷 796-808页

作者： Michels, Adalberto Sato Lopes, Thiago Cantos Stall Sikora, Celso Gustavo Magatao, Leandro Fed Univ Technol Parana UTFPR Grad Program Elect & Comp Engn CPGEI Curitiba Parana Brazil Univ Hamburg Hamburg Business Sch Inst Operat Res Hamburg Germany

Multi-manned assembly lines are commonly found in industries that manufacture large-size products (e.g. automotive industry), in which multiple workers are assigned to the same station in order to perform different operations simultaneously on the same product. Although the balancing problem of multi manned assembly lines had been modelled before, the previously presented exact mathematical formulations are only able to solve few small-size instances, while larger cases are solved by heuristics or metaheuristics that do not guarantee optimality. This work presents a new mixed-integer linear programming model with strong symmetry break constraints and decomposes the original problem into a new Benders' Decomposition Algorithm to solve large instances optimally. The proposed model minimises the total number of workers along the line and the number of opened stations as weighted primary and secondary objectives, respectively. Besides, feasibility cuts and symmetry break constraints based on combinatorial Benders' cuts and model's parameters are applied as lazy constraints to reduce search-space by eliminating infeasible sets of allocations. Tests on a literature dataset have shown that the proposed mathematical model outperforms previously developed formulations in both solution quality and computational processing time for small-size instances. Moreover, the proposed Benders' Decomposition Algorithm yielded 117 optimal results out of a 131-instances dataset. Compared to previously presented methods, this translates to 19 and 25 new best solutions reached for medium and large-size instances, respectively, of which 19 and 23 are optimal solutions. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Combinatorial optimisation Multi-manned assembly line balancing Benders' decomposition Combinatorial Benders' cuts mixed-integer linear programming

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Three methods for robust grading

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第1期272卷 364-371页

作者： Burer, Samuel Piccialli, Veronica Dept Management Sci S346 Pappajohn Business Bldg Iowa City IA 52242 USA Univ Roma Tor Vergata Dipartimento Ingn Civile & Ingn Informat Via Politecn 1 I-00133 Rome Italy

We propose three strategies by which a professor of a university course can assign final letter grades taking into account the natural uncertainty in students' individual assignment and final numerical grades. The first strategy formalizes a common technique that identifies large gaps in the final numerical grades. For the second and third strategies, we introduce the notion of a borderline student, that is, a student who is close to, but below, the breakpoint for the next highest letter grade. Using mixed-integer linear programming and a tailor-made branch-and-bound algorithm, we choose the letter-grade breakpoints to minimize the number of borderline students. In particular, the second strategy treats the uncertainty implicitly and minimizes the number of borderline students, while the third strategy uses a robust-optimization approach to minimize the maximum number of borderline students that could occur based on an explicit uncertainty set. We compare the three strategies on realistic instances and identify overall trends as well as some interesting exceptions. While no strategy appears best in all cases, each can be computed in a reasonable amount of time for a moderately sized course. Moreover, they collectively provide the professor important insight into how uncertainty affects the assignment of final letter grades. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Robust optimization mixed-integer linear programming Branch-and-bound Grading Higher education

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