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IEEE 20th International Conference on Automation Science and Engineering (CASE)

作者： Gunawan, Aldy Salsabila, Nabila Yuraisyah Minh, Nguyen Pham Kien Yu, Vincent F. Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore Natl Taiwan Univ Sci & Technol Dept Ind Management Taipei Taiwan

ISBN: (纸本)9798350358513;9798350358520

This study proposes a home healthcare routing and scheduling problem, where perishable products such as medicines, vaccines, or meals must be provided for some patients' treatments. The problem is formulated as a mixed integer linear programming (MILP). A two-stage matheuristic is then developed as the solution approach. The first stage is a local search to solve the nurse routing problem, and the second stage is run as the relaxed MILP to solve the scheduling problem. The matheuristic is tested on newly generated instances and compared with the results of CPLEX. It is able to obtain CPLEX solutions within shorter computational times for small instances and achieve feasible solutions for larger instances.

关键词： mixed-integer linear programming

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A Multi-objective Optimization Problem for Sizing and Siting of Power Systems with the Integration of DG Units, EV Charging Stations, and ESSs 67

A Multi-objective Optimization Problem for Sizing and Siting...

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67th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Aliamooei-Lakeh, Saeed Corzine, Keith Parsa, Leila de Castro, Ricardo Univ Calif Santa Cruz Jack Baskin Sch Engn Santa Cruz CA 95064 USA Univ Calif Merced Dept Mech Engn Merced CA USA

ISBN: (纸本)9798350387186;9798350387179

In this paper, a multi-objective optimization problem of sizing and siting power systems with the integration of electric vehicles in a distribution system is addressed. Vehicle-to-grid contribution, charging stations, renewable energy sources in the form of photovoltaic and wind turbines, and energy storage systems are considered in the proposed approach. A mixed-integer linear programming model is presented for this problem, which minimizes the total cost associated with infrastructure development and power generation while considering operational efficiency and sustainability considerations. A strategic placement of such infrastructural arrangements and their sizes can improve grid resiliency and optimally host a high penetration of electric vehicles, along with integrating renewable energy sources, is also proposed. The suitability of the proposed model is proven through a case study presented for an IEEE 24-bus distribution power system, drawing improvements in cost effectiveness, energy efficiency, and renewable energy utilization within the power grid.

关键词： Electric vehicles mixed-integer linear programming renewable energy sources Sizing and siting vehicle-to-grid

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Enhancing Data Processing Throughput in IoT-Edge-Cloud Systems using Optimized Task Placement 44

Enhancing Data Processing Throughput in IoT-Edge-Cloud Syste...

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44th IEEE International Conference on Distributed Computing Systems (ICDCS)

作者： Choudhary, Vishal Wang, Peng Sourav, Suman Chen, Binbin Singapore Univ Technol & Design Ctr Smart Syst CS2 Singapore Singapore Singapore Univ Technol & Design Informat Syst Technol & Design Pillar ISTD Singapore Singapore

ISBN: (纸本)9798350386066;9798350386059

The rapid growth of Internet-of-Things (IoT) systems demands higher throughput to process sensor data. Existing data processing platforms use simple heuristics for task placement, which perform poorly. We proposed a Permutation-based Task Placement Optimizer (PTPO) that constructs a set of valid task placement permutations to formulate a mixed-integer linear programming problem. PTPO enables efficient real-time task placement for multiple dynamic applications. Our study highlights three key design factors: joint consideration of compute and network constraints, accurate profiling of resource needs, and fine-grained splitting of tasks across nodes. We demonstrate more than 80% throughput gain compared to state-of-the-art schemes using real-world IoT Applications.

关键词： mixed-integer linear programming

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A mixed-integer Conic Program for the Moving-Target Traveling Salesman Problem based on a Graph of Convex Sets

A Mixed-Integer Conic Program for the Moving-Target Travelin...

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2024 International Conference on Intelligent Robots and Systems

作者： Philip, Allen George Ren, Zhongqiang Rathinam, Sivakumar Choset, Howie Texas A&M Univ Dept Mech Engn College Stn TX 77843 USA Shanghai Jiao Tong Univ 800 Dongchuan Rd Shanghai Peoples R China Carnegie Mellon Univ 5000 Forbes Ave Pittsburgh PA 15213 USA

ISBN: (纸本)9798350377712;9798350377705

This paper introduces a new formulation that finds the optimum for the Moving-Target Traveling Salesman Problem (MT-TSP), which seeks to find a shortest path for an agent, that starts at a depot, visits a set of moving targets exactly once within their assigned time-windows, and returns to the depot. The formulation relies on the key idea that when the targets move along lines, their trajectories become convex sets within the space-time coordinate system. The problem then reduces to finding the shortest path within a graph of convex sets, subject to some speed constraints. We compare our formulation with the current state-of-the-art mixed integer Conic Program (MICP) formulation for the MT-TSP. The experimental results show that our formulation outperforms the MICP for instances with up to 20 targets, with up to two orders of magnitude reduction in runtime, and up to a 60% tighter optimality gap. We also show that the solution cost from the convex relaxation of our formulation provides significantly tighter lower-bounds for the MT-TSP than the ones from the MICP.

关键词： mixed-integer linear programming

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Blockchain-backed resilient strategies in a stochastic supply chain sourcing and distribution environment under disruption: implications for B2B sector

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JOURNAL OF BUSINESS & INDUSTRIAL MARKETING 2025年第1期40卷 223-249页

作者： Manzoor, Rizwan Sahay, B. S. Gumte, Kapil Singh, Sujeet Kumar Inst Management Technol Ghaziabad Dept Operat & Supply Chain Ghaziabad India Indian Inst Management Jammu Dept Operat & Supply Chain Jammu India Indian Stat Inst Hyderabad SQC & OR Hyderabad India

PurposeWith the changing landscape of the globalised business world, business-to-business supply chains face a turbulent ocean of disruptions. Such is the effect that supply chains are disrupted to the point of failure, supply is halted and its adverse effect is seen on the consumer. While previous literature has extensively studied risk and resilience through mathematical modelling, this study aims to envision a novel supply chain model that integrates blockchain to support visibility and recovery resilience ***/methodology/approachThe stochastic bi-objective (cost and shortage utility) optimisation-based mixed-integer linear programming model integrates blockchain through a binary variable, which activates at a particular threshold risk-averse level of the ***, visibility is improved, as identified by the average reduction of penalties by 36% over the different scenarios. Secondly, the average sum of shortages over different scenarios is consequently reduced by 36% as the recovery of primary suppliers improves. Thirdly, the feeling of shortage unfairness between distributors is significantly reduced by applying blockchain. Fourthly, unreliable direct suppliers resume their supply due to the availability of timely information through blockchain. Lastly, reliance on backup suppliers is reduced as direct suppliers recover *** limitations/implicationsThe findings indicate that blockchain can enhance visibility and recovery even under high-impact disruption conditions. Furthermore, the study introduces a unique metric for measuring visibility, i.e. penalty costs (lower penalty costs indicate higher visibility and vice versa). The study also improves upon shortages and recoveries reported in prior literature by 6%. Finally, blockchain application caters to the literature on shortage unfairness by significantly reducing the feeling of shortage unfairness among *** implicationsThis study establi

关键词： Supply chain risk B2B supply chain Supply chain disruption Supply chain resilience Risk aversion Blockchain technology mixed-integer linear programming

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Sustainable Development Index Using MILP to Assign Relative Weight To Different UNSDG Parameters 18th

Sustainable Development Index Using MILP to Assign Relative...

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18th International Conference on Learning and Intelligent Optimization, LION 2024

作者： Shah, Keyaan Dhirubhai Ambani International School Mumbai400098 India

ISBN: (纸本)9783031756221

This report presents a novel approach to quantifying and comparing national efforts towards the United Nations Sustainable Development Goals (UNSDGs) by developing a Sustainable Development Index (SDI) using mixed-integer linear programming (MILP). The methodology uniquely integrates MILP to optimize the weighting of various sustainability indicators, offering a robust and mathematical foundation for the SDI. This approach not only captures the discrete and linear aspects of sustainability indicators but also aligns the resulting index with existing measures such as the Human Development Index (HDI) and Environmental Performance Index (EPI). Through meticulous data collection, normalization, and MILP-based analysis, the report examines 17 unique indicators, each representing a specific UNSDG. The study employs advanced optimization tools, including Gurobi Optimizer and Julia programming language, to compute the SDI, ensuring an objective and reliable comparison of countries’ sustainability performances. The report reveals insightful findings, with the SDI offering a clear and quantifiable measure of progress towards the UNSDGs. The outcome of this research has significant implications for policymakers, researchers, and the public, providing a nuanced understanding of national sustainability efforts. It underscores the utility of MILP in addressing complex global challenges and sets a precedent for future research in sustainable development assessment. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： mixed-integer linear programming

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Research on Two-Stage Distributed Robust Optimization Scheduling of Electric Thermal Hydrogen Integrated Energy System Considering Stepped Carbon Trading 11th

Research on Two-Stage Distributed Robust Optimization Schedu...

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11th Frontier Academic Forum of Electrical Engineering, FAFEE 2024

作者： Zhou, Junsong Dang, Cunlu School of Electrical Engineering and Information Engineering Lanzhou University of Technology Lanzhou730050 China

ISBN: (纸本)9789819787791

To effectively address the uncertain risks posed by the inherent intermittency and volatility of wind and solar power output to the Electricity-Heat-Hydrogen Integrated Energy System (EHH-IES) and to reduce carbon emissions, a two-stage distributionally robust optimization scheduling model considering a stepwise carbon trading mechanism is proposed. Firstly, the accurate characterization of the probability distribution of wind and solar power output fuzzy sets is achieved by combining the Wasserstein distance, solving the uncertainty issue of wind and solar power output on the EHH-IES. Secondly, a stepwise carbon trading mechanism is introduced to reduce the carbon emissions of the EHH-IES through policy guidance and economic incentives. Thirdly, for the EHH-IES, a day-ahead and intra-day two-stage distributionally robust optimization scheduling model based on the probability distribution fuzzy set is constructed, and it is transformed into a mixed-integer linear programming model for solving using linear decision rules and strong duality theory. Finally, simulation validation is conducted based on actual wind and solar power data. The results prove that the stepwise carbon trading can significantly reduce the carbon emissions of the EHH-IES, and the proposed model can further ensure robustness under the uncertainty risk of wind and solar power while considering the economy of the EHH-IES. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： mixed-integer linear programming

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Energy Management for Prepaid Customers: A linear Optimization Approach

Energy Management for Prepaid Customers: A Linear Optimizati...

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2024 International Conference on Communications Control and Computing Technologies for Smart Grids

作者： Marathe, Maitreyee Roald, Line A. Univ Wisconsin Madison Dept Elect & Comp Engn Madison WI 53706 USA

ISBN: (纸本)9798350318562;9798350318555

With increasing energy prices, low income households are known to forego or minimize the use of electricity to save on energy costs. If a household is on a prepaid electricity program, it can be automatically and immediately disconnected from service if there is no balance in its prepaid account. Such households need to actively ration the amount of energy they use by deciding which appliances to use and for how long. We present a tool that helps households extend the availability of their critical appliances by limiting the use of discretionary ones, and prevent disconnections. The proposed method is based on a linear optimization problem that only uses average power demand as an input and can be solved to optimality using a simple greedy approach. We compare the model with two mixed-integer linear programming models that require more detailed demand forecasts and optimization solvers for implementation. In a numerical case study based on real household data, we assess the performance of the different models under different accuracy and granularity of demand forecasts. Our results show that our proposed linear model is much simpler to implement, while providing similar performance under realistic circumstances.

关键词： mixed-integer linear programming

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OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models 41

OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers ...

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41st International Conference on Machine Learning (ICML)

作者： AhmadiTeshnizi, Ali Gao, Wenzhi Udell, Madeleine Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA Stanford Univ Inst Computat & Math Engn Stanford CA USA

Optimization problems are pervasive in sectors from manufacturing and distribution to healthcare. However, most such problems are still solved heuristically by hand rather than optimally by state-of-the-art solvers because the expertise required to formulate and solve these problems limits the widespread adoption of optimization tools and techniques. This paper introduces OptiMUS, a Large Language Model (LLM)-based agent designed to formulate and solve (mixed integer) linear programming problems from their natural language descriptions. OptiMUS can develop mathematical models, write and debug solver code, evaluate the generated solutions, and improve its model and code based on these evaluations. OptiMUS utilizes a modular structure to process problems, allowing it to handle problems with long descriptions and complex data without long prompts. Experiments demonstrate that OptiMUS outperforms existing state-of-the-art methods on easy datasets by more than 20% and on hard datasets (including a new dataset, NLP4LP, released with this paper that features long and complex problems) by more than 30%. The implementation and the datasets are available at https://***/teshnizi/OptiMUS.

关键词： mixed-integer linear programming

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Social-economic and environment impacts for a fish reverse supply chain: A mixed integer linear optimization approach

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CLEANER LOGISTICS AND SUPPLY CHAIN 2024年 13卷

作者： Vanany, Iwan Wangsa, Ivan Darma Savitri, Niken Anggraini Putera, Rizki Revianto Cholili, Muhammad Wibawa, Berto Mulia Atmaja, Lukman Tseng, Ming-Lang Inst Teknol Sepuluh Nopember Dept Ind & Syst Engn Surabaya Indonesia Inst Teknol Sepuluh Nopember Dept Business Management Surabaya Indonesia Inst Teknol Sepuluh Nopember Dept Chem Surabaya Indonesia Asia Univ Inst Innovat & Circular Econ Taichung Taiwan

This study contributes to the fish reverse supply chain due to a lack of social, economic and environmental impacts. This study aims to develop a mathematical model for the fish reverse supply chain with a multi-echelon, multiple periods, and products. The model optimizes total profit, job opportunities, and carbon emissions simultaneously. The proposed model provides social-economic insight for governments and industries to understand the increasing job opportunities if fish gelatine and powder industries can process fish waste. A sensitivity analysis shows that the supply of raw fish, selling prices, and purchasing costs are sensitive to total profit, carbon emissions, and job opportunities. The results show that the total profit for five months is USD 1,437,837, and the most significant contribution to the total cost is the costs of purchasing, emission costs, and production costs, which are 43.83%, 24.02%, and 18.15%, respectively. These results can assist managers in making optimal decisions regarding raw fish supply, halal fish gelatine, and fish powder production, impacting strategic, tactical, and operational policies.

关键词： Reverse supply chain mixed-integer linear programming environmental Impacts Social-economic insight Carbon emissions

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