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Designing a collaborative maintenance planning mechanism between airline and maintenance company using a bilevel model - Considering flexible maintenance schedule and service charges

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartB期255卷

作者： Qin, Yichen Ng, Kam K. H. Sun, Xuting Yao, Senna Wen, Xin Shanghai Maritime Univ Sch Econ & Management Shanghai 201306 Peoples R China Hong Kong Polytech Univ Dept Aeronaut & Aviat Engn Hung Hom Hong Kong Peoples R China Shanghai Univ SILC Business Sch Shanghai 201899 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hung Hom Hong Kong Peoples R China

Periodic aircraft Maintenance Repair and Overhaul (MRO) activities are compulsory. To capture the features of MRO operations between airline and maintenance company under MRO outsourcing mode, we consider a collaborative aircraft maintenance planning problem, in which the airline outsources its self-operated maintenance checks to an independent maintenance company. Under such context, MRO planning conflicts between two collaborates exists especially during maintenance peak period, as airline aims to maximize flight operations revenues by receiving timely MRO service. On the other hand, maintenance company strives to accomplish heterogenous demands without causing tardiness and involving excessive MRO resources cost. Therefore, finding an effective mechanism to eliminate the conflicts between maintenance demands (from airline company) and maintenance service supply capability (from maintenance company) is indispensable for collaboration. A bi-level optimization model is formulated to describe the conflicting objectives and maintenance planning features of two independent stakeholders. To facilitates a synchronization of demand and supply and reconcile MRO conflicts, flexible maintenance schedules and service charges decisions from two independent collaborators is involved in the model, enabling a maintenance planning negotiation for finding mutual beneficial maintenance plan. An iterative algorithm deploying bounding updating strategy is developed, which generates a series of convergentoriented bounding constraints along the iterative negotiation and guides the adjustment of maintenance demand and supply towards equilibrium. Based on the computational results in solving various maintenance planning scenarios, the impacts of different features (e.g. resource availability, resource demands level, and penalty cost of service tardiness) on airline and service company 's planning performance are analysed, revealing that maintenance service company 's own interest can be a

关键词： Bi-level optimization mixed -integer linear programming Collaborative maintenance planning MRO outsourcing Flexible schedule and charges

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The potential of residential load flexibility: An approach for assessing operational flexibility

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2024年 158卷

作者： Akbari, Saeed Lopes, Rui Amaral Martins, Joao NOVA Univ Lisbon NOVA Sch Sci & Technol Dept Elect & Comp Engn Caparica Portugal Ctr Technol & Syst UNINOVA CTS P-2829516 Caparica Portugal Associated Lab Intelligent Syst LASI P-2829516 Caparica Portugal

This study presents a novel methodology for evaluating the flexibility of residential electricity consumers under diverse operational conditions introducing innovative flexibility indicators. The increasing demand for energy flexibility from the demand side is crucial for ensuring the power grid's economic stability and resilience. Buildings offer a range of potential flexibility sources that can be effectively leveraged for this purpose. Accordingly, this paper formulates energy flow management in a Smart House using a mixed-integer linear programming (MILP) framework, incorporating the scheduling of shiftable appliances and an Energy Storage System (ESS). By defining different consumption strategies, the feasible region for Energy-Time Profiles (ETPs) is explored through the establishment of the corresponding optimization problems. A series of case studies are presented to evaluate the impact of operational constraints on the feasible region. Finally, by meticulously analyzing the characteristics of ETPs extracted from these case studies, the proposed flexibility indicators are introduced, quantifying the Smart House's energy flexibility potential. Furthermore, a sensitivity analysis is conducted to scrutinize the influence of key parameters on the new flexibility indicator, encompassing ESS characteristics. The findings substantiate the efficacy of the proposed indicators in providing comprehensive insights into the potential energy flexibility under a range of operational conditions.

关键词： Energy flexibility Energy management Demand side management Smart house mixed -integer linear programming

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An emission control policymaking model for sustainable river transportation

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TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE 2024年 181卷

作者： Zhen, Lu Zhang, Shuanglu Dan, Zhuge Wang, Shuaian Wang, Yong Shanghai Univ Sch Management Shanghai Peoples R China Hong Kong Polytech Univ Dept Logist & Maritime Studies Kowloon Hong Kong Peoples R China Chongqing Jiaotong Univ Sch Econ & Management Chongqing Peoples R China

Sustainable river transportation is an important component in the development of green transportation. Emission control policymaking in rivers is a key measure for realizing sustainable river transportation. Transportation demand for an origin-destination pair of cities along a river may involve transferring between land transportation and water transportation. This study takes this into account by using a mathematical programming methodology to propose a model for emission control policymaking for sustainable river transportation that minimizes the total emissions produced by both land transportation and river transportation. The model supports government regulators in making heterogeneous emission control area (ECA) policies for a river, which is shown to be superior to a traditional homogeneous ECA policy. A branch-and-bound algorithm is also developed to solve the model. Using two of China's main rivers, a case study is conducted to derive computational results that may be potentially useful for government regulators in policymaking.

关键词： Emission control Model for policymaking Sustainable river transportation mixed -integer linear programming Branch and bound

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A socio-economic and quality-oriented optimal fruit supply chain network design in a multi-market and multi-product environment: A real case study

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SOCIO-ECONOMIC PLANNING SCIENCES 2024年 94卷

作者： Javanmardan, Ahvan Golpira, Heris Baradaran, Vahid Islamic Azad Univ Dept Ind Engn North Tehran Branch Tehran Iran Islamic Azad Univ Dept Ind Engn Sanandaj Branch Sanandaj Iran

This paper focuses on developing an optimal sustainable fruit Closed -Loop Supply Chain (CLSC). A novel multiobjective mixed -integer linear programming (MILP) model is suggested to formulate a multi -product, multimarket, multi -period, multi -level, multi -mode selling problem which aims to minimize cost and emissions and maximize the whole social segments ' responsiveness to fruit, vinegar, and compost. The model is solved by the LP -metric method and implemented in a real case in Iran. The findings indicate that achieving the highest level of responsiveness comes with a substantial cost for the network. However, this does not apply to environmental considerations. For decision -makers prioritizing sustainability, the proposed decision support system strongly advises against buying fruit from fruit cars. Due to the absence of positive impacts on the level of responsiveness, buying from fruit cars results in increased costs and emissions. For a cost- and environmentally -sensitive decision -maker, it is recommended to provide higher -quality fruits. Because the lower the quality of the fruit, leads to increased waste rates and emissions. Meeting increased vinegar demand, with its elevated costs and emissions, becomes justifiable only when the policymaker is actively seeking to achieve maximum responsiveness.

关键词： Fruit supply chian Closed -loop supply chain Sustainability mixed -integer linear programming Lp-metric

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A sustainable-circular citrus closed-loop supply chain configuration: Pareto-based algorithms

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023年第1期328卷 116892页

作者： Goodarzian, Fariba Ghasemi, Peiman Gonzalez, Ernesto DR. Santibanez Tirkolaee, Erfan Babaee Univ Seville Sch Engn Org Engn Grp Camino Descubrimientos S-N Seville 41092 Spain Univ Vienna Dept Business Decis & Analyt Kolingasse 14-16 A-1090 Vienna Austria Univ Talca Fac Ingn Talca1 Poniente1141 Talca Chile Istinye Univ Dept Ind Engn TR-34396 Istanbul Turkiye

Configuration of sustainable supply chains for agricultural products has been a well-known research field recently which is continuing to evolve and grow. It is a complex network design problem, and despite the abundant literature in the field, there are still few models offered to integrate social impacts and environmental effects to support network design decision-making to support the configuration of the citrus supply chain. In this work, the citrus supply chain design problem is investigated by integrating the production, distribution, in-ventory control, recycling and locational decisions in which the triple bottom lines of sustainability, as well as circularity strategy, are addressed. Accordingly, a novel multi-objective mixed-integer linear programming (MILP) model is proposed to formulate a multi-period multi-echelon problem to design the sustainable citrus Closed-Loop Supply Chain (CLSC) network. To solve the developed model, the epsilon-constraint approach is employed in small-sized problems. Furthermore, Strength Pareto Evolutionary Algorithm II (SPEA-II) and Pareto Envelope -based Selection Algorithm II (PESA-II) algorithms are used in medium-and large-sized problems. Taguchi design technique is then utilized to adjust the parameters of the algorithms efficiently. Three well-known assessment metrics and convergence analysis are regarded to test the efficiency of the suggested algorithms. The numerical results demonstrate that the SPEA-II algorithm has a superior efficiency over PESA-II. Moreover, to validate the applicability of the developed methodology, a real case study in Mazandaran/Iran is investigated with the help of a set of sensitivity analyses.

关键词： Citrus supply chain Closed -loop supply chain network Sustainability Circularity mixed -integer linear programming Meta -heuristic algorithms

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Accelerated dual dynamic integer programming applied to short-term power generation scheduling

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年 145卷

作者： dos Santos, Kenny Vinente Colonetti, Bruno Finardi, Erlon Cristian Zavala, Victor M. Univ Fed Amazonas Dept Oil & Gas 6200 Gen RodrigoOctavio AvCoroado 1 BR-69080900 Manaus Amazonas Brazil Univ Fed Santa Catarina Dept Elect & Elect Engn BR-88040900 Florianopolis SC Brazil INESC P&D Brasil BR-11055300 Santos SP Brazil Univ Wisconsin Dept Chem & Biol Engn 1415 Engn Dr Madison WI 53706 USA

The short-term generation scheduling (STGS) problem defines which units must operate and how much power they must deliver to satisfy the system demand over a planning horizon of up to two weeks. The problem is typically formulated as a large-scale mixed-integer linear programming problem, where off-the-shelf commercial solvers generally struggle to efficiently solve realistic instances of the STGS, mainly due to the large-scale of these models. Thus, decomposition approaches that break the model into smaller instances that are more easily handled are attractive alternatives to directly employing these solvers. This paper proposes a dual dynamic integer programming (DDiP) framework for solving the STGS problem efficiently. As in the standard DDiP approach, we use a nested Benders decomposition over the time horizon but introduce multiperiod stages and overlap strategies to accelerate the method. Simulations performed on the IEEE-118 system show that the pro-posed approach is significantly faster than standard DDiP and can deliver near-optimal solutions.

关键词： Dual dynamic integer programming Short-term generation scheduling mixed -integer linear programming

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Scheduling quay cranes and shuttle vehicles simultaneously with limited apron buffer capacity

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COMPUTERS & OPERATIONS RESEARCH 2023年 151卷

作者： Yin, Yu-Qi Zhong, Meisu Wen, Xin Ge, Ying-En Shanghai Maritime Univ Sch Econ & Management Shanghai Peoples R China Changan Univ Sch Econ & Management Xian Shaanxi Peoples R China Jiangsu Univ Sci & Technol Sch Econ & Management Zhenjiang Jiangsu Peoples R China Changan Univ Coll Transportat Engn Xian Shaanxi Peoples R China

How to schedule quay cranes (QCs) and shuttle vehicles (SVs) simultaneously or model them in an integrated scheduling problem is one of the most important problems in operations and management of a container terminal. This paper investigates an integrated QC and SV scheduling problem constrained by apron buffer capacity. In this problem, the decisions to make include the bay-to-QC assignment, the QC-bay sequence, the QC-job sequence, the job-to-SV assignment and the SV-job sequence. First, a mixed-integer linear programming model is formulated for this problem to minimize the makespan. Second, the relationships and interactive variables among the four segments of constraints of the proposed model (i.e., scheduling QCs for vessel bays, sequencing jobs handled by a QC in each bay, scheduling SVs for jobs, apron buffer capacity constraints for each vessel bay) are analyzed to present three rules: vessel block rule, near-to-far rule and full-buffer rule. Finally, a sequential insertion algorithm, a greedy insertion algorithm and an improved genetic algorithm are proposed to solve midand large-sized cases for the problem. Numerical experiments show that the algorithms perform well, compared to the off-the-shelf solver. Based on these experiments, managerial implications are discussed for container terminal operations and management.

关键词： Container terminal Quay crane Shuttle vehicle Integrated scheduling problem mixed -integer linear programming Block buffer zone Automated stacking

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Model-based energy management systems: Weighting of multiobjective functions using the Volatile Energy Prices Scalarization (VEPS)

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COMPUTERS & CHEMICAL ENGINEERING 2023年 169卷

作者： Fuhrmann, Florian Schirrer, Alexander Kozek, Martin Tech Univ Wien Inst Mech & Mechatron Getreidemarkt 9-BA A-1060 Vienna Austria

Predictive energy management systems (EMSs) enable industrial plants to operate the energy supply systems at optimal efficiency, taking account of multiple objectives, including energy cost reduction. The performance of model-based EMSs depends on the appropriate design and correct scalarization of the resulting multiobjective function. This paper introduces the Volatile Energy Prices Scalarization (VEPS) method, which effectively de-signs, standardizes, and weighs the multiobjective function of model-based EMSs without the need for prior simulations or test runs. We present a case study, in which we compare the VEPS method to other state-of-the-art methods, utilizing a validated simulation model from an industrial food plant. The results show that the VEPS method outperforms other weighting methods with comparable tuning effort in this case-study. Moreover, the performance of the VEPS method is close to the Pareto-optimal performance. Economic weighting methods such as VEPS enable a fast and cost-effective implementation of EMS in the manufacturing industry.

关键词： Energy management system Model predictive control Multiobjective optimization mixed -integer linear programming Thermal batch processes

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MILP-based load shedding strategy for mitigating FIDVR phenomenon in smart networks

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年 146卷

作者： Ghotbi-Maleki, Mahdi Chabanloo, Reza Mohammadi Javadi, Hamid Shahid Beheshti Univ Dept Elect Engn Tehran Iran

Fault-induced delayed voltage recovery (FIDVR) phenomenon refers to delayed voltage recovery after the occurrence of a fault on the transmission level, caused by the presence of induction motor (IM) loads at the distribution level. Load shedding (LS), which reduces the imbalance of the requested and generated power in the network, is one of the most effective ways to deal with the FIDVR. This paper proposed a wide-area LS strategy based on the voltage estimation process. At first, a process for online voltage estimation is presented using threeorder model of IM and modified Gauss-Seidel load flow. This process is used to identify FIDVR-involved buses and verify the calculated amounts and locations of loads to be shed. These variables are calculated through a repetition-based optimization problem, linearized and converted to mixed-integer linear programming form to reduce calculation time. The proposed LS strategy is implemented on the IEEE 118-bus network and the simulation results confirm the efficiency of the proposed method compared to previous ones. The proposed strategy could mitigate the critical FIDVR of all buses with less load to be shed from fewer buses.

关键词： Fault -induced delayed voltage recovery Gauss -Seidel load flow Load shedding Voltage estimation Smart network mixed -integer linear programming

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Optimal component sizing and operational optimisation of a mobile energy system for decentralised electricity supply

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SMART ENERGY 2023年 11卷

作者： Roth, Maximilian Franke, Georg Rinderknecht, Stephan Tech Univ Darmstadt Inst Mechatron Syst Mech Engn Otto Berndt Str 2 D-64287 Darmstadt Germany

The ambitious legislation driven by climate change, makes it necessary to focus more strongly on previously untapped greenhouse gas saving potentials, such as the mobile supply of renewable electrical energy which can create geographical flexibility. Consumers are supplied with electrical energy by the mobile energy system, whereby the energy can potentially come from the photovoltaic modules (PV), the diesel generator (DG), the fuel cell (FC) or the battery (EES) contained in the overall system. Exemplary customers of the service can be, e.g., road construction sites, festivals or other temporary events or also local distribution grid balancing applications. Given exogenous PV production and load profiles, this study determines the cost-optimal sizing of the system components (FC, DG, and EES) while deriving the optimal operating strategy for the overall system using mixed integer linear programming (MILP). In addition to investment and fuel costs, emission costs are integrated, which primarily occur in the context of DG operation. The model is implemented in Python in the optimisation envi-ronment Pyomo and solved by the Gurobi solver. The simulation is based on three scenarios for different com-binations of PV production and load profiles as well as various hydrogen and emission price scenarios. It turns out, that the optimal sizes of the FC and the DG are between 0.5 and 2 kW for 60% and 0% demand coverage through PV respectively. For the battery, an optimal size between 1 and 4.8 kWh can be derived analogously.

关键词： Microgrid scheduling Microgrid sizing mixed -integer linear programming Optimisation Smart energy system

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