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Learning dispatching rules using random forest in flexible job shop scheduling problems

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2019年第10期57卷 3290-3310页

作者： Jun, Sungbum Lee, Seokcheon Chun, Hyonho Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA Boston Univ Dept Math & Stat Boston MA 02215 USA

In this paper, we address the flexible job-shop scheduling problem (FJSP) with release times for minimising the total weighted tardiness by learning dispatching rules from schedules. We propose a random-forest-based approach called Random Forest for Obtaining Rules for Scheduling (RANFORS) in order to extract dispatching rules from the best schedules. RANFORS consists of three phases: schedule generation, rule learning with data transformation, and rule improvement with discretisation. In the schedule generation phase, we present three solution approaches that are widely used to solve FJSPs. Based on the best schedules among them, the rule learning with data transformation phase converts them into training data with constructed attributes and generates a dispatching rule with inductive learning. Finally, the rule improvement with discretisation improves dispatching rules with a genetic algorithm by discretising continuous attributes and changing parameters for random forest with the aim of minimising the average total weighted tardiness. We conducted experiments to verify the performance of the proposed approach and the results showed that it outperforms the existing dispatching rules. Moreover, compared with the other decision-tree-based algorithms, the proposed algorithm is effective in terms of extracting scheduling insights from a set of rules.

关键词： flexible job shop random forest genetic algorithm machine learning discretisation mixed-integer linear programming

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GoNDEF: an exact method to generate all non-dominated points of multi-objective mixed-integer linear programs

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OPTIMIZATION AND ENGINEERING 2019年第1期20卷 89-117页

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

Most real-world problems involve multiple conflicting criteria. These problems are called multi-criteria/multi-objective optimization problems (MOOP). The main task in solving MOOPs is to find the non-dominated (ND) points in the objective space or efficient solutions in the decision space. A ND point is a point in the objective space with objective function values that cannot be improved without worsening another objective function. In this paper, we present a new method that generates the set of ND points for a multi-objective mixed-integer linear program (MOMILP). The Generator of ND and Efficient Frontier (GoNDEF) for MOMILPs finds that the ND points represented as points, line segments, and facets consist of every type of ND point. First, the GoNDEF sets integer variables to the values that result in ND points. Fixing integer variables to specific values results in a multi-objective linear program (MOLP). This MOLP has its own set of ND points. A subset of this set establishes a subset of the ND points set of the MOMILP. In this paper, we present an extensive theoretical analysis of the GoNDEF and illustrate its effectiveness on a set of instance problems.

关键词： Multi-objective optimization mixed-integer linear programming Non-dominated point Exact method

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A Decentralized Framework for the Optimal Coordination of Distributed Energy Resources

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第1期34卷 349-359页

作者： Anjos, Miguel F. Lodi, Andrea Tanneau, Mathieu Ecole Polytech Montreal Dept Math & Ind Engn Montreal PQ H3T 1J4 Canada Grp Etud & Rech Anal Decis Montreal PQ H3T 1J4 Canada

Demand-response aggregators are faced with the challenge of how to best manage numerous and heterogeneous distributed energy resources (DERs). This paper proposes a decentralized methodology for optimal coordination of DERs. The proposed approach is based on Dantzig-Wolfe decomposition and column generation, thus allowing to integrate any type of resource whose operation can be formulated within a mixed-integer linear program. We show that the proposed framework offers the same guarantees of optimality as a centralized formulation, with the added benefits of distributed computation, enhanced privacy, and higher robustness to changes in the problem data. The practical efficiency of the algorithm is demonstrated through extensive computational experiments, on a set of instances generated using data from Ontario energy markets. The proposed approach was able to solve all test instances to proven optimality, while achieving significant speed-ups over a centralized formulation solved by state-of-the-art optimization software.

关键词： Column generation Dantzig-Wolfe decomposition demand response aggregation distributed energy resources mixed-integer linear programming smart grid

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Optimal design of an oil pipeline with a large-slope section

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ENGINEERING OPTIMIZATION 2019年第9期51卷 1480-1494页

作者： Wang, Bohong Yuan, Meng Yan, Yamin Yang, Ke Zhang, Haoran Liang, Yongtu China Univ Petr Natl Engn Lab Pipeline Safety MOE Key Lab Petr Engn Beijing Peoples R China China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Beijing Peoples R China Univ Tokyo Ctr Spatial Informat Sci Chiba Japan

One of the important issues in the operation of a long-distance oil pipeline in a large-slope area is pressure control, especially for the section after the turning point. In this study, a method to optimally design an oil pipeline with a large-slope section is proposed. The method is based on a stochastic mixed-integer linear programming model with minimal total cost as the objective function to determine the size of the pipeline, the location, the operational plan of pump stations and the location of pressure reduction stations. Hydraulic calculations and different types of oil product are considered. The uncertainty in flow rates of the pipeline is studied by the proposed stochastic programming approach. This method is applied to a real case of designing an oil product pipeline in a large-slope area.

关键词： Oil pipeline large slope design pressure control mixed-integer linear programming

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Corridor level cooperative trajectory optimization with connected and automated vehicles

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2019年 105卷 405-421页

作者： Yu, Chunhui Feng, Yiheng Liu, Henry X. Ma, Wanjing Yang, Xiaoguang Tongji Univ Minist Educ Key Lab Rd & Traff Engn 4800 Caoan Rd Shanghai Peoples R China UMTRI 2901 Baxter Rd Ann Arbor MI 48109 USA Univ Michigan Dept Civil & Environm Engn 2320 GG Brown2350 Hayward St Ann Arbor MI 48109 USA

Trajectory planning for connected and automated vehicles (CAVs) has been studied at both isolated intersections and multiple intersections under the fully CAV environment in the literature. However, most of the existing studies only model limited interactions of vehicle trajectories at the microscopic level, without considering the coordination between vehicle trajectories. This study proposes a mixed-integer linear programming (MILP) model to cooperatively optimize the trajectories of CAVs along a corridor for system optimality. The car-following and lane-changing behaviors of each vehicle along the entire path are optimized together. The trajectories of all vehicles along the corridor are coordinated for system optimality in terms of total vehicle delay. All vehicle movements (i.e., left-turning, through, and right-turning) are considered at each intersection. The ingress lanes are not associated with any specific movement and can be used for all vehicle movements, which provides much more flexibility. Vehicles are controlled to pass through intersections without traffic signals. Due to varying traffic conditions, the planning horizon is adaptively adjusted in the implementation procedure of the proposed model to find a balance between solution feasibility and computational burden. Numerical studies validate the advantages of the proposed CAV-based control over the coordinated fixed-time control at different demand levels in terms of vehicle delay and throughput. The analyses of the safety time gaps for collision avoidance within intersection areas show the promising benefits of traffic management under the fully CAV environment.

关键词： Connected and automated vehicle Trajectory optimization and coordination Corridor mixed-integer linear programming

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Heuristic Approaches to Solve E-Scooter Assignment Problem

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IEEE ACCESS 2019年 7卷 175093-175105页

作者： Masoud, Mahmoud Elhenawy, Mohammed Almannaa, Mohammed H. Liu, Shi Qiang Glaser, Sebastien Rakotonirainy, Andry Queensland Univ Technol CARRS Q Brisbane Qld 4000 Australia King Saud Univ Civil Engn Dept Riyadh 11451 Saudi Arabia Fuzhou Univ Sch Econ & Management Fuzhou 350108 Peoples R China

Nowadays, rapid urbanization causes a wide-range of congestion and pollution in megacities worldwide, which bears an urgent need for micromobility solutions such as electric scooters (e-scooter). Many e-scooter firms use freelancers to charge the scooter where they compete to collect and charge the e-scooters at their homes. This competition leads the chargers to travel long distances to collect e-scooters. In this paper, we developed a mixed-integer linear programming (MILP) model for a real-world e-scooter-Chargers Allocation (ESCA) problem. The proposed model allocates the e-scooters to the chargers with an emphasis on minimizing the chargers' average travelled distance to collect the e-scooters. The MILP returns optimal solutions in most cases;however, the ESCA is identified as a generalized assignment problem which classifies as an NP-complete combinatorial optimization problem. Moreover, we modelled the charging problem as a game between two sets of disjoint players, namely e-scooters and chargers. Then we adapted the college admission algorithm (ACA) to solve the ESCA problem. For the sake of comparison, we applied the black hole optimizer (BHO) algorithm to solve this problem using small and medium cases. The experimental results show that the ACA solutions are close to the optimal solutions obtained by the MILP. Furthermore, the BHO solutions are not as good as the ACA solutions, but the ACA solution consumes more time to solve large-scale real cases. Based on the obtained results, we recommend applying the ACA1 to find the near-optimal solution for large-scale instances, as the MILP is inapplicable to find the exact solution in comparison.

关键词： Micromobility modes e-scooter-chargers allocation mixed-integer linear programming heuristic

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Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control

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ENERGY 2019年 179卷 1302-1319页

作者： Wakui, Tetsuya Sawada, Kento Yokoyama, Ryohei Aki, Hirohisa Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan Univ Tsukuba Fac Engn Informat & Syst 1-1-1 Tennodai Tsukuba Ibaraki 3058573 Japan

Predictive management for energy supply networks using photovoltaics generation (PV) units, heat pump water-heating units (HPUs), and battery units is developed by uniquely combining two-stage stochastic schedule programming and rule-based control to enhance their operating performances, including operating cost reduction under low selling prices of the surplus PV output after a feed-in tariff system and uncertain input conditions. The forecast scenarios of input conditions are generated from the probability distributions at each sampling time. The schedule planning problem is formulated using two stage stochastic mixed-integer linear programming and solved by inputting the forecast scenarios and the initial operation states of network components. In the operation control, the energy flow rates are modulated according to the actual input conditions under the obtained operation schedule. The forecast scenario generation and stochastic schedule planning are updated using a receding horizon approach. The developed management is applied to an annual operating simulation of a residential energy supply network for a housing complex, consisting of a shared PV unit, four sets of an HPU and thermal storage tank, and shared battery unit. The simulation results reveal that the decrease in the annual operating cost reduction by the developed management from the ideal management based on the previously-known PV output is just 1.57% point. Moreover, at the selling price of the surplus PV output higher than 6 yen/kWh, the developed management has an advantage in the annual operating cost over the charging- and exporting-priority managements. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Energy management Model predictive control Energy supply network Microgrid Two-stage stochastic programming mixed-integer linear programming

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Profitability of active retrofitting of multi-apartment buildings: Building-attached/integrated photovoltaics with special consideration of different heating systems

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ENERGY AND BUILDINGS 2019年 190卷 86-102页

作者： Fina, Bernadette Auer, Hans Friedl, Werner Tech Univ Wien Energy Econ Grp Gusshausstr 25-29E370-3 A-1040 Vienna Austria Austrian Inst Technol Giefinggasse 4 A-1210 Vienna Austria

Multi-apartment buildings comprise almost half of the European housing stock and are for the most part old and energy inefficient, making active retrofitting an important topic. The objective of this paper is to determine the profitability and optimal size of different technology portfolios for renewable building energy. A mixed-integer linear programming optimisation model is developed in Matlab with the objective of maximising the Net Present Value over a time horizon of 20 years. To examine multiple use cases, a modular approach is used for realising different multi-apartment building set-ups. Building-attached and building-integrated photovoltaic systems on different parts of the building skin already achieve breakeven. Heat pumps, pellet and district heating can hardly compete with gas heating yet. However, heat pumps have synergy effects with PV systems, thus reinforcing their implementation, as does a tenant portfolio with a good correlation with the sunshine hours. The profitability gap between investment costs for passive building renovation and resulting energy cost savings is significant. However, it is the smallest for buildings with quality standards. In conclusion, governmental subsidies and financial incentives such as the true cost pricing of CO2 emissions are necessary to trigger investments in reasonable combinations of passive and active retrofitting measures. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Retrofitting Multi-apartment building Net Present Value mixed-integer linear programming Electricity and heating technologies Building-attached/integrated photovoltaics

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A mathematical model and algorithms for the aircraft hangar maintenance scheduling problem

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APPLIED MATHEMATICAL MODELLING 2019年 67卷 491-509页

作者： Qin, Yichen Wang, Z. X. Chan, Felix T. S. Chung, S. H. Qu, T. Jinan Univ Sch Elect & Informat Engn Zhuhai Campus Zhuhai 519070 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Peoples R China Dongbei Univ Finance & Econ Sch Business Adm Dalian Peoples R China

An aircraft hangar maintenance scheduling problem is studied, motivated by the aircraft heavy maintenance conducted in a hangar operated by an independent maintenance service company. The aircraft hangar maintenance scheduling problem in such context consists of determining a maintenance schedule with minimum penalty costs in fulfilling maintenance requests, and a series of hangar parking plans aligned with the maintenance schedule through the planning period. A mixed-integer linear programming (MILP) mathematical model, integrating the interrelations between the maintenance schedule and aircraft parking layout plans, is presented at first. In the model, the variation of parking capacity of the maintenance hangar and the blocking of the aircraft rolling in and out path are considered. Secondly, the model is enhanced by narrowing down the domain of the time-related decision variables to the possible rolling in and out operations time of each maintenance request. Thirdly, to obtain good quality feasible solutions for large scale instances, a rolling horizon approach incorporating the enhanced mathematical model is presented. The results of computational experiments are reported, showing: (i) the effectiveness of the event-based discrete time MILP model and (ii) the scalability of the rolling horizon approach that is able to provide good feasible solutions for large size instances covering a long planning period. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Aircraft maintenance scheduling Hangar parking layout planning mixed-integer linear programming Event-based model Rolling horizon approach

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Sharing Energy Storage Between Transmission and Distribution

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第1期34卷 152-162页

作者： Elliott, Ryan T. Fernandez-Blanco, Ricardo Kozdras, Kelly Kaplan, Josh Lockyear, Brian Zyskowski, Jason Kirschen, Daniel S. Univ Washington Dept Elect Engn Seattle WA 98195 USA Univ Malaga Dept Appl Math Malaga 29076 Spain Doosan GridTech Seattle WA 98104 USA Snohomish Cty PUD Everett WA 98206 USA

This paper addresses the problem of how best to coordinate, or "stack," energy storage services in systems that lack centralized markets. Specifically, its focus is on how to coordinate transmission-level congestion relief with local, distribution-level objectives. We describe and demonstrate a unified communication and optimization framework for performing this coordination. The congestion relief problem formulation employs a weighted l(1)-norm objective. This approach determines a set of corrective actions, i.e., energy storage injections and conventional generation adjustments, that minimize the required deviations from a planned schedule. To exercise this coordination framework, we present two case studies. The first is based on a 3-bus test system, and the second on a realistic representation of the Pacific Northwest region of the United States. The results indicate that the scheduling methodology provides congestion relief, cost savings, and improved renewable energy integration. The large-scale case study informed the design of a live demonstration carried out in partnership with the University of Washington, Doosan GridTech, Snohomish County PUD, and the Bonneville Power Administration. The goal of the demonstration was to test the feasibility of the scheduling framework in a production environment with real-world energy storage assets. The demonstration results were consistent with computational simulations.

关键词： Distribution system operator energy storage system mixed-integer linear programming state of charge transmission congestion transmission system operator unit commitment

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