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IISE Annual Conference and Expo 2024

作者： Akbarian-Saravi, Niloofar Akbarian-Saravi, Ali Rabbani, Masoud School of Industrial Engineering College of Engineering University of Tehran Tehran Iran School of Industrial Engineering Amirkabir University of Technology Tehran Iran

ISBN: (纸本)9781713877851

Renewable energies have gained a significant attraction due to the increasing growing demand for energy and environmental concerns. As one of the alternatives to fossil fuels, bioethanol from switchgrass is considered. To realize the strategic and tactical biofuel supply chain decisions, in this study, we developed a different mixed-integer linear programming model aiming to minimize total annualized costs over a 5-year planning horizon by incorporating financial incentives and comparing the models with and without budget consideration. Using this model, the optimal allocation of material flows is determined along with optimal supply and pre-processing locations for producing a gasoline (95%)-ethanol (5%) blend. The monetary incentives include i) a constant budget for the whole Bioethanol Supply Chain (BSC) planning;and ii) treating the distribution of the budget as a decision variable. To illustrate the application of the proposed model, a case study of Iran is investigated. Results indicate the requirement of a monetary incentive to produce bioethanol and establish plants for bioethanol processing. The cost savings resulting from the optimal allocation of monetary incentives were higher than those from constant monetary incentives. The sensitivity analysis of the model indicates that the biomass-to-ethanol conversion rate has the highest impact on the total costs. © IISE Annual Conference and Expo *** rights reserved.

关键词： mixed-integer linear programming

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Optimal override policy for chemotherapy scheduling template via mixed-integer linear programming

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OPTIMIZATION LETTERS 2022年第5期16卷 1549-1562页

作者： Huang, Yu-Li Sikder, Ishtiak Xu, Guanglin Mayo Clin Robert & Patricia E Kern Ctr Sci Hlth Care Delive Rochester MN USA Univ N Carolina Dept Syst Engn & Engn Management Charlotte NC 28223 USA

Owing to treatment complexity in chemotherapy administration, nurses are usually required at the beginning, end, and at certain times during the treatment period to ensure high-quality infusion. It is, thus, critical for an outpatient chemotherapy unit to design a scheduling template that can effectively match nursing resources with treatment requirements. The template contains appointment slots of different lengths and thus allows schedulers to place patients into these slots according to the provider's order. As the template is often used over a period of several months, there usually exists a mismatch between the daily patient mix and the fixed structure of the given template. Hence, override policies must be employed to adjust to demand. However, these policies are often manually performed by schedulers. We propose a mixed-integer linear programming model to systematically develop optimal override policies in place of the manual process to improve template utilization while maintaining template stability. Numerical experiments based on real-life data from a chemotherapy unit are conducted to demonstrate the effectiveness of the proposed approach.

关键词： Chemotherapy Scheduling template Override policy mixed-integer linear programming

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A mixed-integer linear programming model with multi-unit strategy for distributed biorefinery superstructures with economic and social benefits

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CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY 2022年第6期24卷 1903-1925页

作者： Maharana, Debasis Kommadath, Remya Kotecha, Prakash Indian Inst Technol Guwahati Dept Chem Engn Gauhati 781039 Assam India Indian Inst Technol Guwahati Sch Business Gauhati 781039 India

Biofuels have emerged as a promising alternative for depleting fossil fuels. Efficient biofuel production requires the optimal supply chain design and the planning of complex production operations in biorefineries. The biomass processing is capacity constrained due to design restrictions. The limitation on the production capacity corresponding to a selected technology restricts the maximum production from the most profitable process. In such a scenario, the production plan involves the use of less profitable processes to satisfy the demand, resulting in a sub-optimal solution. This article proposes a multi-unit, multi-period supply chain model to overcome the restriction in plant capacity by establishing multiple units of a profitable process. The multi-objective optimization study of the proposed model has been demonstrated on a case study from the literature that requires the design of supply chain for bioenergy. The proposed formulation leads to solutions with better economic and social benefits than those reported in the literature. The multi-unit model provides a solution which has a 4.73% increase in profit and generates 78 additional jobs for a horizon of 12 months. The optimal network design has contributed to several key findings, such as the breakeven point of the raw materials with respect to the profit and the dual relationship between profit and the number of jobs generated. The study also analyzes the effect of multiple units and variations of demand on the proposed model. The multi-unit model is able to determine a solution with 3.96% improvement in profit even with a reduction in the demand by 50%. [GRAPHICS] .

关键词： Biofuel supply chain Facility location Capacity planning Social impact Economic optimization mixed-integer linear programming

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A mixed-integer linear programming formulation for the modular layout of three-dimensional connected systems

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MATHEMATICS AND COMPUTERS IN SIMULATION 2022年第0期201卷 739-754页

作者： O'Neill, Sam Wrigley, Paul Bagdasar, Ovidiu Univ Derby Dept Elect Comp & Math Kedleston Rd Derby DE22 1GB England

Given the considerable complexity of process plants, there has been a great deal of research focused on aiding the design of plant layout through mathematical optimisation, i.e. optimising the positioning of the equipment in the plant for space and cost efficiency. Recently, the use of modular approaches within the construction industry, whereby work is performed off-site before being assembled on-site, has become a popular and powerful way of reducing build schedules and costs. Modular approaches have many other real applications where items must be packed to minimise the connections between them (e.g. piping, wiring, modular office and factory layouts) and consider the modular layout of the system. In this paper, we provide a formulation of the problem that, in addition to the standard layout problem, considers a modular block layout to allow modular construction and transportation of the plant. The problem is represented as a directed network, with the aim to pack the items into predefined containers and minimise the rectilinear distance between the connected items. We propose mixed-integer linear programming (MILP) models for the 2-dimensional and 3-dimensional problems and solve them using the state-of-the-art mathematical programming solver, Gurobi. Because of the combinatorial nature of the problem, solutions involving a large number of items may not converge and a suboptimal solution must be considered. However, our results suggest that even in the case of optimising a large number of items, the suboptimal solutions found after a reasonable number of iterations where deemed, by a domain expert, to be a good enough starting point to continue the design process, especially in the early concept phase. (c) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词： Floor packing Bin packing Facility layout mixed-integer linear programming MILP Process plant design

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Exact Complexity Certification of Suboptimal Branch-and-Bound Algorithms for mixed-integer linear programming 22

Exact Complexity Certification of Suboptimal Branch-and-Boun...

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22nd World Congress of the International Federation of Automatic Control (IFAC)

作者： Shoja, Shamisa Axehill, Daniel Linkoping Univ Div Automat Control Linkoping Sweden

ISBN: (纸本)9781713872344

In this paper, we present a method to exactly certify the computational complexity of standard suboptimal branch-and-bound (B&B) algorithms for computing suboptimal solutions to mixed-integer linear programming (MILP) problems. Three well-known approaches for suboptimal B&B are considered. This work shows that it is possible to exactly certify the computational complexity also when these approaches are used. Moreover, it also enables to compute exact bounds on the level of suboptimality actually to be obtained online, also for methods previously without any such guarantees. It additionally provides a novel deeper insight into how they affect the performance of the B&B algorithm in terms of the required computation time and memory storage. The exact bounds on the online worst-case computational complexity (e.g., the accumulated number of LP solver iterations or size of the B&B tree) and the worst-case suboptimality computed with the proposed method are very relevant for real-time applications such as Model Predictive Control (MPC) for hybrid systems. The numerical experiments confirm the correctness of the proposed method, and they demonstrate the usefulness of the certification method for certification of a standard online B&B-based MILP solver employing the three considered suboptimal techniques. Copyright (c) 2023 The Authors.

关键词： Numerical methods for optimal control Optimal control of hybrid systems mixed-integer linear programming Branch and bound method Complexity certification Suboptimal solutions

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mixed-integer linear programming Model to Assess Lithium-Ion Battery Degradation Cost

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ENERGIES 2022年第9期15卷 3060-3060页

作者： Oliveira, Debora B. S. Gloria, Luna L. Kraemer, Rodrigo A. S. Silva, Alisson C. Dias, Douglas P. Oliveira, Alice C. Martins, Marcos A. I. Ludwig, Mathias A. Gruner, Victor F. Schmitz, Lenon Coelho, Roberto F. CERTI Fdn Ctr Sustainable Energy BR-88040900 Florianopolis SC Brazil AES Brazil R&D & Innovat BR-04578000 Sao Paulo Brazil Univ Fed Santa Catarina Dept Elect Engn BR-88040900 Florianopolis SC Brazil

This work proposes a mixed-integer linear programming model for the operational cost function of lithium-ion batteries that should be applied in a microgrid centralized controller. Such a controller aims to supply loads while optimizing the leveled cost of energy, and for that, the cost function of the battery must compete with the cost functions of other energy resources, such as distribution network, dispatchable generators, and renewable sources. In this paper, in order to consider the battery lifetime degradation, the proposed operational cost model is based on the variation in its state of health (SOH). This variation is determined by experimental data that relate the number of charge and discharge cycles to some of the most important factors that degrade the lifespan of lithium-ion batteries, resulting in a simple empirical model that depends on the battery dispatch power and the current state of charge (SOC). As proof-of-concept, hardware-in-the-loop (HIL) simulations of a real microgrid are performed considering a centralized controller with the proposed battery degradation cost function model. The obtained results demonstrate that the proposed cost model properly maintains the charging/discharging rates and the SOC at adequate levels, avoiding accelerating the battery degradation with use. For the different scenarios analyzed, the battery is only dispatched to avoid excess demand charges and to absorb extra power produced by the non-dispatchable resources, while the daily average SOC ranges from 48.86% to 65.87% and the final SOC converges to a value close to 50%, regardless of the initial SOC considered.

关键词： battery energy storage system degradation cost model lithium-ion battery microgrid power dispatch mixed-integer linear programming

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mixed-integer linear programming model for tree-like pipeline scheduling problem with intermediate due dates on demands

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OPERATIONAL RESEARCH 2020年第1期20卷 399-425页

作者： Taherkhani, M. Seifbarghy, M. Tavakkoli-Moghaddam, R. Fattahi, P. Islamic Azad Univ Dept Ind Engn Sci & Res Branch Tehran Iran Alzahra Univ Fac Engn Dept Ind Engn Tehran Iran Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Arts & Metier Paris Tech Ctr Metz LCFC Metz France

Multi-product pipelines are a significant and extensive mean of transporting petroleum based products from refineries to distribution centers. Previous contributions on tree-like pipeline scheduling problem have considered a simple structure with a single refinery connected to a mainline and some secondary lines only emerged from the mainline. In practice, however, a tree-like pipeline may also have several branches on a secondary line resulting in a complex structure, the so called multi-level tree-like pipeline. This paper addresses the short-term scheduling of multi-level tree-like pipelines with multiple refineries through a continuous time mixed-integer linear programming (MILP) model that considers multiple intermediate due dates for product demands. The objective is to satisfy product demands on time at the minimum operational costs, such as pumping, interface and backorder costs. The proposed model performance's is shown by solving four examples.

关键词： Multi-product pipelines Tree-like structure Scheduling mixed-integer linear programming

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Support vector machines within a bivariate mixed-integer linear programming framework

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 245卷

作者： Warwicker, John Alasdair Rebennack, Steffen Karlsruhe Inst Technol Inst Operat Res IOR D-76185 Karlsruhe Baden-wurttembe Germany

Support vector machines (SVMs) are a powerful machine learning paradigm, performing supervised learning for classification and regression analysis. A number of SVM models in the literature have made use of advances in mixed-integer linear programming (MILP) techniques in order to perform this task efficiently. In this work, we present three new models for SVMs that make use of piecewise linear (PWL) functions. This allows effective separation of data points where a simple linear SVM model may not be sufficient. The models we present make use of binary variables to assign data points to SVM segments, and hence fit within a recently presented framework for machine learning MILP models. Alongside presenting an inbuilt feature selection operator, we show that the models can benefit from robust inbuilt outlier detection. Experimental results show when each of the presented models is effective, and we present guidelines on which of the models are preferable in different scenarios.

关键词： Support vector machine Optimisation mixed-integer linear programming Outlier detection Feature selection

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Hybrid Quantum Benders' Decomposition For mixed-integer linear programming

Hybrid Quantum Benders' Decomposition For Mixed-integer Line...

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IEEE Wireless Communications and Networking Conference (IEEE WCNC)

作者： Zhao, Zhongqi Fan, Lei Han, Zhu Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA Univ Houston Dept Engn Technol Houston TX 77004 USA

ISBN: (纸本)9781665442664

The Benders' decomposition algorithm is a technique in mathematical programming for complex mixed-integer linear programming (MILP) problems with a particular block structure. The strategy of Benders' decomposition can be described as a strategy of divide and conquer. The Benders' decomposition algorithm has been employed in a variety of applications such as communication, networking, and machine learning. However, the master problem in Benders' decomposition is still NP-hard, which motivates us to employ quantum computing. In the paper, we propose a hybrid quantum-classical Benders' decomposition algorithm. We transfer the Benders' decomposition's master problem into the quadratic unconstrained binary optimization (QUBO) model and solve it by the state-of-the-art quantum annealer. Then, we analyze the computational results and discuss the feasibility of the proposed algorithm. Due to our reformulation in the master problem in Benders' decomposition, our hybrid algorithm, which takes advantage of both classical and quantum computers, can guarantee the solution quality for solving MILP problems.

关键词： Benders' Decomposition mixed-integer linear programming Hybrid Quantum-Classical Computing Quantum Computing Communication Networking

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Comparative Economic Optimization for an Overseas Hydrogen Supply Chain Using mixed-integer linear programming

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ACS SUSTAINABLE CHEMISTRY & ENGINEERING 2021年第42期9卷 14249-14262页

作者： Kim, Ayeon Kim, Heehyang Lee, Hyunjun Lee, Boreum Lim, Hankwon Ulsan Natl Inst Sci & Technol Sch Energy & Chem Engn Ulsan 44919 South Korea Yale Univ Dept Chem & Environm Engn New Haven CT 06520 USA Ulsan Natl Inst Sci & Technol Dept Energy Engn Ulsan 44919 South Korea

As environmental problems become serious, many countries have been striving to change fossil-based energy to renewable and sustainable hydrogen energy. However, there are large capacity differences for each country's hydrogen production, making hydrogen trading necessary. Although extensive research has investigated hydrogen technologies and economics, to the best of our knowledge, no study has examined the optimization of the overall hydrogen supply chain, from overseas supply to domestic consumption, considering various feasibility scenarios. This is a case study on the hydrogen supply chain for South Korea, which is expected to be one of the major hydrogen-importing countries, considering the decarbonized hydrogen requirements of the importing country and the production capacities of exporting countries over two decades. This study's optimized results for a hydrogen supply chain via mixed-integer linear programming reveal that it is most feasible for South Korea to import blue hydrogen from Qatar and Russia and green hydrogen from UAE and India, using liquefied hydrogen in the near term. This is because of the significantly lesser resource prices compared to other countries. The share of blue hydrogen supply dominates in the near term, while the green hydrogen supply is expected to gradually prevail over blue hydrogen due to an exponential drop in the renewable electricity price. With the price drop of green hydrogen, green hydrogen purchases from other countries in tandem with the UAE are predicted, rather than the blue hydrogen supply, considering that long-term demand will exceed the UAE's predicted capacity.

关键词： Overseas H-2 supply chain Economic analysis Case study mixed-integer linear programming

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