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Designing drone delivery networks for vaccine supply chain: a case study of Niger

IISE TRANSACTIONS ON HEALTHCARE SYSTEMS ENGINEERING 2024年第3期14卷 193-213页

作者： Eksioglu, Sandra D. Proano, Ruben A. Kolter, Maximilian Nurre Pinkley, Sarah Univ Arkansas Dept Ind Engn Fayetteville AR 72701 USA Rochester Inst Technol Dept Ind & Syst Engn Rochester NY USA

This research aims to evaluate the use of drones to deliver pediatric vaccines in remote areas of low-income and low-middle-income countries. Delivering vaccines in these regions is challenging because of the inadequate road networks and long transportation distances that make it difficult to maintain the cold chain's integrity during delivery. We propose a mixed-integer linear program to determine the location of drone hubs to facilitate vaccine delivery. The model considers the operational attributes of drones, vaccine wastage in the supply chain, cold storage, and transportation capacities. We develop a case study using data from Niger to determine the impact of drone deliveries in improving vaccine availability. Based on our numerical analysis, regional centers should be considered potential locations for drone hubs. We demonstrate that outreach sessions supported by drone deliveries of vaccines can improve vaccine availability. These improvements depend on the available budget to build drone hubs and purchase drones, available cold storage capacity, and the population density in the study region.

关键词： Drone delivery network vaccine supply chain in low-income and low-middle-income countries mixed-integer linear program Niger's vaccine supply chain

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Scheduling of semi-automatic carousels with fixed production sequences

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2023年第4期61卷 1252-1267页

作者： Campana, Giampaolo Malaguti, Enrico Mele, Mattia Paronuzzi, Paolo Univ Bologna DIN Bologna Italy Univ Bologna DEI Guglielmo Marconi Bologna Italy

Rotary transfer machines are widely used in different industrial sectors. A rich literature concerning their design and optimisation is available, but mainly dedicated to integrated machining systems. This machine architecture is also implemented in the aluminium gravity die casting technology where the specificity of the casting process needs an appropriate design. In particular, the constraints related to processing times and the rigidity of the production sequence impose a specific approach to schedule the production for achieving an optimal cycle time. We approach this problem with an optimisation perspective: first we propose a mixed-integer linear programming formulation for defining the sequencing and scheduling of the machine in order to obtain a specified production with minimum makespan, and discuss strategies for enumerating the variables of the formulation. Second, we describe a heuristic algorithm as an alternative to the solution of the formulation through a general-purpose solver. Eventually, we present extensive computational experiments on a set of instances generated from real data, comparing these alternative approaches.

关键词： Rotary transfer machine gravity die casting scheduling flow-shop mixed-integer linear program heuristics

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An Optimal Layout Pattern-Based Solution Approach to the Extended Machine Layout Problem With Multirow Multicolumn Structure

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2023年第2期20卷 1408-1428页

作者： Qi, Mingyao Hao, Xinru Yuan, Meng Tsinghua Univ Shenzhen Int Grad Sch Div Logist & Transportat Shenzhen 518055 Peoples R China Alibaba Grp Hangzhou 311121 Peoples R China

The machine layout problem (MLP) is to determine the optimal location arrangement of machines in a production system, usually in order to minimize the total material transmission distance. This article considers a type of MLP in an automated manufacturing system with unequal-area machines, machine replicas, and taking multi-row multi-column layout structure. The aim is to determine the near-optimal machine layout and orbit layout simultaneously. We model the problem as a mixed-integer linear program by introducing the concept of orbit-based relative locations and using auxiliary binary variables, including relative location assignment variables, in-block relationship variables, and material routing variables. We further exploit the optimal layout patterns, based on which, when the relative locations of the machines and orbits are given, we can quickly derive the near-optimal absolute machine and orbit positions without solving a mixed-integer linear program. A two-layer hybrid heuristic method is proposed to solve the problem: the outer layer is a variable neighborhood search metaheuristic used to explore the solution space of the relative locations, while the inner layer is a recursive heuristic based on the optimal layout patterns. Experiments on instances of different sizes are conducted, and the effectiveness and efficiency of the proposed algorithms are verified. Note to Practitioners-Many manufacturing systems, for example, those in the semiconductor industry, use automated guided vehicles running on orbits to transfer materials between machines. The design of such a manufacturing system consists of determining the numbers of vertical and horizontal orbits, their positions, and the positions of all machines. It is not unusual for there to be hundreds of machines. Furthermore, machines of the same type can be deployed non-adjacently in an automated transfer context since materials can easily be transmitted to an arbitrary machine. The flexibility and complexity

关键词： Layout Orbits Manufacturing systems Power transmission lines Costs Production Metaheuristics Machine layout automated manufacturing orbits unequal area mixed-integer linear program recursive

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An ultra-fast optimization algorithm for unit commitment based on neural branching

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ENERGY REPORTS 2023年 9卷 1112-1120页

作者： Sun, Yi Wu, Jun Zhang, Guofang Zhang, Lei Li, Ran State Grid Sichuan Elect Power Co Sichuan 610041 Peoples R China Shanghai Jiao Tong Univ Sch Smart Energy Shanghai 200240 Peoples R China

The computational efficiency of unit commitment (UC) is important for power system operations. Traditionally the unit commitment problem is solved per hour in a day, but with the scale of the power system and the electricity market continuing to expand, the large-scale UC problem will be hard to be solved within 1 h which will affect the power system operation and market clearing. To reduce the solving time of the large-scale UC problem, an ultra-fast optimization algorithm of neural branching for unit commitment (NBUC) is proposed. NBUC learns the branch and bound (B&B) decision made by full strong branching (FSB), which can generate the perfect B&B order to minimize the iterative process but take a lot of time to decide the perfect order by using graph convolutional neural network according to the historical data, and then makes the perfect order prediction with a certain precision without spending a lot of time to make B&B decision which minimizes the solving time including the iteration time and decision time in order to solve the large-scale UC problem quickly. A modified RTS-96 bus system is used to validate the effectiveness of the proposed NBUC. The results show 9.3% and 23.2% reductions in computational time compared with commercial software CPLEX and SCIP. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Unit commitment mixed-integer linear program Branch-and-bound Graph convolutional neural network Neural branching

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Collaborative traveling salesman problem with ground vehicle as a charger for unmanned aerial vehicle

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TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH 2023年第7期15卷 707-721页

作者： Cha, Hyungjoo Kim, DongKyun Eun, Joonyup Cheong, Taesu Korea Univ Sch Ind Management Engn Seoul South Korea Korea Univ Grad Sch Management Technol Seoul South Korea

Innovation in logistics industry is now implicit, and the use of unmanned aerial vehicles is at the center of logistics innovation. To effectively utilize unmanned aerial vehicles for last-mile delivery, collaborative delivery using ground vehicles and unmanned aerial vehicles has recently been investigated. However, previous studies neglected proper management of batteries, assuming their constant replacement whenever unmanned aerial vehicles land, and hence numerous batteries are required for unmanned aerial vehicles. Given this research gap, we present a new routing model for collaborative delivery wherein an unmanned aerial vehicle uses a ground vehicle as a power source. A mathematical formulation is presented, and noticing the complexity, a heuristic algorithm is developed. We present a case study to verify the operational efficiency of the model. We test the performance of the heuristic and draw insights based on geographical locations of customers via computational experiments.

关键词： Electric unmanned aerial vehicle traveling salesman problem collaborative delivery mixed-integer linear program Heuristics

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Optimizing automotive inbound logistics: A mixed-integer linear programming approach

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2022年第0期163卷

作者： Baller, Reinhard Fontaine, Pirmin Minner, Stefan Lai, Zhen Audi AG Auto union Str 1 D-85057 Ingolstadt Germany Catholic Univ Eichstatt Ingolstadt Ingolstadt Sch Management Schanz 49 D-85049 Ingolstadt Germany Tech Univ Munich TUM Sch Management Arcisstr 21 D-80333 Munich Germany Munich Data Sci Inst MDSI Walther Von Dyck Str 10 D-85748 Garching Germany Nio GmbH Montgelasstr 14 D-81679 Munich Germany

The optimization of inbound logistics from first-tier suppliers at the aggregation level of a factory is a challenging coordination problem. In practice, different transport modes and multiple constraints exist and need to be taken into account: the available number of storage places, capacity of goods-entry, delivery profile and transportation pattern constraints, truck utilization, demand satisfaction, and the reverse flow of empty load carriers. A scalable solution method that is tailored to an automotive factory is currently not available. Optimization is usually carried out manually, e.g. experience-based or by using decision trees that follow an iterative optimization approach. Most of the mathematical models in the literature only deal with parts of the requirements and do not validate results in the required complexity. We present a mixed-integer linear programming approach to solve this complex problem using Gurobi. The solution capability and quality are enhanced by the introduction of a cyclic inventory constraint and valid inequalities. The evaluation of the approach is based on a case study of a German automotive factory with 570 suppliers and 3927 stock keeping units and reduces the as-is total cost by 33.86%. Additionally, CO2 emissions are reduced by 74.66%. We further show that variable order quantities, along with a courier and express service as an additional transport mode, are of high economic relevance. As part of a sensitivity analysis, we show how the total costs change, when (a) goods-entry handling constraints, (b) truck utilization, (c) storage constraints, or (d) transportation costs vary, and (e) the effect of a cyclic inventory constraint.

关键词： Automotive logistics Total landed costs Transportation pattern Shipment coordination mixed-integer linear program

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Approximating Input-Output Curve of Pumped Storage Hydro Plant: A Disjunctive Convex Hull Method

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IEEE TRANSACTIONS ON POWER SYSTEMS 2023年第1期38卷 63-74页

作者： Wang, Siyuan Liu, Jian Bo, Rui Chen, Yonghong Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA Midcontinent Independent Syst Operator Inc Carmel IN 46032 USA

Pumped storage hydro (PSH) plant is a valuable resource with storage and fast ramp capabilities, which can manage the intermittency of renewable energy. An accurate model for the input-output curve of PSH plant can capture its varying efficiency feature and enable accurate evaluations of available generating/pumping capability. However, the trade-off between approximation accuracy and computation time poses a significant challenge for input-output curve modeling. In this paper, we develop a hypograph-relaxation-based input-output curve modeling framework, wherein sufficient conditions for exact hypograph relaxation are defined, proved, and analyzed for fixed-speed PSH considering the value of water in the upper reservoir. Under this framework, a novel disjunctive convex hull model is proposed to balance the aforementioned trade-off. Our model can take advantage of high accuracy in time-consuming piece-wise approximation models, and acceptable computation burden in less-accurate convex hull models. To divide a given input-output curve into various components that can be approximated by their respective convex hulls, we propose to use an approximate convex decomposition (ACD) based approach. The proposed model is tested for profit maximization problems using real-world Ludington PSH station data. Numerical results demonstrated the superior computational advantage of the proposed approach.

关键词： Pumped storage hydro input-output curve hypograph relaxation disjunctive convex hull mixed-integer linear program

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Power System Restoration With Renewable Participation

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2023年第2期14卷 1112-1121页

作者： Qiu, Feng Zhang, Yichen Yao, Rui Du, Pengwei Argonne Natl Lab Energy Syst Div Lemont 60439 IL USA Univ Texas Arlington Dept Elect Engn Arlington TX 76019 USA Google Mountain View CA 94043 USA Elect Regulat Council Texas ERCOT Austin TX 78744 USA

Power system restoration requires initial power sources to restart generators, energizing transmissions, and pick up critical loads. Sufficient initial power capacity is critical for restoration success and reducing outage duration. Due to the reliability requirement and high standby costs, black-start resources are scarce and expensive in areas where hydro power is not available. Variable renewable energy (VRE), whose fast-ramping capability and economical standby costs are suitable for black-start, is traditionally excluded from participation in system restoration because its uncertainty and variability could cause severe disturbance to the system that is already fragile during restoration. Recently, VRE is becoming a potential participant in system restoration as auxiliary black-start resources. This work will explore the potential benefits of renewable energy in restoration and potential ways for VRE to participate in system restoration. We propose two dispatch models for wind participation. The uncertainty of wind generation is handled by probabilistic constraints to guarantee a feasible restoration plan with a high probability. We perform computational experiments to demonstrate the effectiveness of proposed models and benefits of renewable participation in restoration with the two approaches.

关键词： Chance constraint data driven mixed-integer linear program wind dispatchability

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Network design for a decarbonised supply chain considering cap-and-trade policy of carbon emissions

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ANNALS OF OPERATIONS RESEARCH 2023年 1-35页

作者： Majumdar, Abhijit Singh, Surya Prakash Jessica, Jessica Agarwal, Aashi Indian Inst Technol Dept Text & Fibre Engn New Delhi 110016 Delhi India Indian Inst Technol Dept Management Studies New Delhi 110016 Delhi India

Decarbonisation of the supply chain necessitates the control of carbon emissions along with the minimisation of cost. This is quite challenging in a multi-echelon supply chain involving multiple suppliers, multiple products, multiple time periods and multimodal transportation. This research deals with the design of a decarbonised supply chain network, under a dynamic environment, considering carbon emissions at various stages of the supply chain. A mixed-integer linear program (MILP) has been developed for a four-echelon supply chain. The problem is solved by using two approaches. The integrated approach, which considers the entire supply chain network as a single entity, yields better results in terms of profitability and more so, when the selling price is lower. Scenario analysis reveals that as the carbon cap reduces, the gross profit shows concomitant reduction and when the former goes below a threshold value, carbon procurement becomes necessary lowering the gross profit further. As the carbon price per unit increases, the gross profit initially decreases and then stabilises. This study contributes by developing an integrated dynamic supply chain network model incorporating carbon emissions at different stages.

关键词： Carbon emissions Decarbonisation mixed-integer linear program Network design Supply chain

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Stochastic arbitrage with market index options

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JOURNAL OF BANKING & FINANCE 2025年 173卷

作者： Beare, Brendan K. Seo, Juwon Zheng, Zhongxi Univ Sydney Sch Econ Sydney NSW 2006 Australia Natl Univ Singapore Dept Econ Singapore 119077 Singapore

Opportunities for stochastic arbitrage in an options market arise when it is possible to construct a portfolio of options which provides a positive option premium and which, when combined with a direct investment in the underlying asset, generates a payoff which stochastically dominates the payoff from the direct investment in the underlying asset. We provide linear and mixed-integer linear programs for computing the stochastic arbitrage opportunity providing the maximum option premium to an investor. We apply our programs to 18 years of data on monthly put and call options on the Standard & Poors 500 index, finding no evidence that stochastic arbitrage opportunities are systematically present. A skewed specification of the underlying market return distribution with a constant market risk premium and constant multiplicative variance risk premium is broadly consistent with the pricing of market index options at moderate strikes.

关键词： linear program mixed-integer linear program Option mispricing Portfolio choice Pricing kernel puzzle Stochastic arbitrage Stochastic dominance

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