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2024 Workshop on Data Science for Agriculture in Africa, DAAfrica 2024

作者： Gbedevi, Akouyo Yvette Atchonouglo, Kossi Lamrous, Sid Ahmed Manier, Marie-Ange Lomé Togo Université de Technologie Belfort-Montbéliard FEMTO-ST Belfort France

The world population is increasing rapidly, and recent awareness of the limits of natural resources and the pollution of soil, air and water, is pushing towards a new form of agriculture, sustainable agriculture. Sustainable agriculture can be defined as an agriculture that combines environmental, social and economic objectives for the well-being of farmers and the soil. Crop rotation took hold during this decade by emphasizing the management of soil resources, while improving economic, environmental and social factors. The goal of the crop rotation planning problem discussed in this paper is to maximize the total net return, with a particular emphasis on incorporating a plant that contributes green manure to the soil alongside nutrient amendments by choosing the best horizon for plannification. The rotations generated are of fixed duration for all the plots and the objective is to maximize the income of the farmers. The results showed that the determined algorithm was feasible. © 2025 Copyright for this paper by its authors.

关键词： mixed-integer linear programming

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Enhancing the Sustainability of Frozen Food Processing: A Production Environment Perspective and Impacts on Quality and Operating Technology 11th

Enhancing the Sustainability of Frozen Food Processing: A Pr...

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11th International Conference on Industrial Engineering and Applications, ICIEA 2024

作者： Chen, Wan Chiao Rau, Hsin Department of Industrial and Systems Engineering Chung Yuan Christian University Taoyuan City32023 Taiwan

ISBN: (纸本)9789819764914

The frozen food sector accounts for a significant share of the food market, a trend that is being fueled by shifting socioeconomic and technical advancements. However, the production process consumes a significant quantity of natural resources and has a particularly high energy demand. Resource depletion and ecological issues are occurring as a result. In response to these challenges, the relationship between the production process and its environmental impact becomes an essential consideration but lacks thorough discussion in the existing research. As a result, the objective of this study is to enhance eco-efficiency in frozen food processing with a focus on the ambient changes trend. Our research first takes the uncertainty of processing surroundings as a process variation and explores its association with quality and operating technology, which are vital factors for first-pass yield. An optimal model then is presented by using mixed-integer linear programming, further enhancing the sustainability of frozen food processing. To verify the effectiveness of the proposed approach, a case study with frozen seafood is conducted and the paper discusses the practical implications of its findings. In this research, the challenge of complex and quantified difficulties with environmental impacts is surmounted, and the study findings present a significant opportunity for the frozen food industry to transition toward sustainability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： mixed-integer linear programming

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Scheduling of forest harvesting operations on multiple cut blocks using multi-task machines

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INTERNATIONAL JOURNAL OF FOREST ENGINEERING 2023年第3期34卷 340-352页

作者： Arora, Rohit Sowlati, Taraneh Mortyn, Joel Univ British Columbia Dept Wood Sci Ind Engn Res Grp 2961-2424 Main Mall Vancouver BC V6T 1Z4 Canada Western Forest Prod Inventory & Anal Vancouver BC Canada

The modernization of forest harvesting operations has significantly increased the cost of machine ownership and has turned forest harvesting into a capital-intensive process. To increase productivity and profitability, some companies have acquired multi-task harvesting machines. While many previous papers focused on optimizing the harvest scheduling to reduce the costs of harvesting, the assignment of multi-task machines was not considered in their models. In this work, an optimization model is developed for the detailed scheduling of harvesting activities on multiple cut blocks using multi-task machines. This model is a continuation of previous work on detailed harvest scheduling. It prescribes the start time and the end time of operations of each machine at each cut block, the number of machines to be assigned for each harvesting activity at each cut block, the cut block that the machine should move to after completing its operation at a cut block, and the type of activity it should perform. It is applied to a case study of a forest company in Canada. According to the results, the total harvesting cost decreased by Can$ 25,000 when multi-task machines were used compared to exclusive machines, due to less machine movement and the need for fewer machines.

关键词： mixed-integer linear programming operational harvest scheduling precedence relationship harvesting costs machine assignment optimization

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Online Cooperative Optimal Power Scheduling of Multiple Microgrids via Hierarchical Imitation Learning 18

Online Cooperative Optimal Power Scheduling of Multiple Micr...

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IEEE 18th International Conference on Control and Automation (ICCA)

作者： Zhao, Yunyi Gao, Shuhua Wang, Jing Li, Congcong Yu, Ming Xiang, Cheng Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore Shandong Univ Sch Control Sci & Engn Jinan 250100 Peoples R China State Grid Shandong Elect Power Co Metering Ctr Mkt Serv Ctr Jinan 250003 Peoples R China Power Automat Pte Ltd Singapore 119968 Singapore

ISBN: (纸本)9798350354416;9798350354409

This paper looks into the issue of optimal power scheduling of multiple microgrids using hierarchical imitation learning. The system is designed to be a hierarchical learning model towards a two-level microgrid community (MGC) structure. The upper-level MGC agent uses an imitation learning algorithm to schedule exchange power between different microgrids, while lower-level microgrid agents are controlled by individual energy management systems using mixed-integer linear programming (MILP). In this paper, we focus on achieving economic dispatch in a large microgrid community while maintaining the privacy of the local microgrids. A simulation study of hierarchical imitation learning is provided based on an MGC system. Our results show the outstanding performance of the designed algorithm with a cost close to the centralized optimal results, about 10% improvement compared to the offline method, and very fast execution, which would be suitable for online power scheduling.

关键词： Energy management imitation learning mixed-integer linear programming microgrid community

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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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Planning of Safe Trajectories in Urban Airspace

Planning of Safe Trajectories in Urban Airspace

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AIAA Aviation Forum

作者： Layer-Reiss, Samuel Kunz, Johanna Bittner, Matthias Holzapfel, Florian Tech Univ Munich Inst Flight Syst Dynam Munich Germany Kempten Univ Appl Sci Allgtiu Res Ctr Kempten Germany Kempten Univ Appl Sci Fac Elect Engn Kempten Germany

ISBN: (数字)9781624107160

ISBN: (纸本)9781624107160

The envisioned concept of Urban Air Mobility (UAM) introduces new challenges for computing safe trajectories. A safe trajectory must ensure that a vertiport to conduct a safety landing is always within reach in the event of a contingency. Moreover, the trajectory must avoid any no-fly zones. Computing optimal trajectories that fulfill both requirements is particularly complicated for areas with numerous no-fly zones and vertiports because the resulting optimization problem involves continuous and discrete variables. As a consequence, the problem cannot be optimized efficiently using collocation- or shooting-based methods. Instead, we propose a linear mixed-integer-based formulation of the problem, which can be solved using mixed-integer linear programming (MILP) solvers. Our approach considers electric Vertical Take-Off and Landing aircraft (eVTOL), which can transition between vertical and wingborne flight. The capabilities of the approach are demonstrated with a two-dimensional example.

关键词： mixed-integer linear programming

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A two-stage matheuristic for the home healthcare routing and scheduling problem with perishable products 20

A two-stage matheuristic for the home healthcare routing and...

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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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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 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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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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