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Multi-objective models for crop rotation planning problems

AGRICULTURAL SYSTEMS 2024年 219卷

作者： Pontes, Roberto Da Silva Gervasio Brandao, Diego Nunes Usberti, Fabio Luiz De Assis, Laura Silva CEFET RJ Fed Ctr Technol Educ Rio De Janeiro Av Maracana 229 BR-20271110 Rio De Janeiro RJ Brazil Univ Estadual Campinas UNICAMP Av Albert Einstein 1251 BR-13083852 Campinas SP Brazil

CONTEXT: Agriculture is a vital component of the global economy and modern societies. It has undergone significant consolidation and transformation in response to the food supply crisis, highlighting the important relationship between humans and the environment. However, concerns remain about food security, particularly with the projected population growth of over 9.5 billion by 2050. The computerization of agri-food supply chains has emerged as a significant response to these challenges. OBJECTIVE: (1) Develop a multi-objective model that explores both net return and crop diversity. (2) Solve the problem using techniques that guarantee optimality. (3) Evaluate the gain in crop diversity versus the net return of the optimized configuration. METHODS: The study presents four Multi-objective mixed-integer linear programming models with integer and binary decision variables for Crop Rotation Planning Problems. The objectives are to maximize net income and increase crop diversity and land utilization. RESULTS AND CONCLUSIONS: The study exclusively employs linear programming techniques to solve the models resulting in an optimal solution. A comparative analysis with existing models in the literature, which primarily focused on maximizing net income, yielded a noteworthy result. The proposed models demonstrate an average increase of 60% in crop diversity, with net return losses of less than 5%. SIGNIFICANCE: In conclusion, this research provides valuable information for crop rotation planning and highlights the importance of agricultural farm management and precision agriculture in addressing current challenges. The innovative nature of this research is exemplified by the use of mixed-integer linear programming techniques to solve a multi-objective problem with integer and binary variables. The obtained results demonstrate increased crop diversity and minimal economic losses, which have significant implications for several areas of agricultural science, policy, and practic

关键词： Multi-objective optimization Precision farming Crop rotation mixed-integer linear programming Agricultural farm management

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Assessing production fulfillment time risk: application to pandemic-related health equipment

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2023年第24期61卷 8401-8422页

作者： Soltanisehat, Leili Ghorbani-Renani, Nafiseh Gonzalez, Andres D. Barker, Kash Univ Oklahoma Sch Ind & Syst Engn Norman OK 73019 USA

Manufacturing companies strive to identify and manage the effects of unexpected disruptions (risks) on their production processes, which affect their performance and resilience. In this study, we propose a decision framework to capture the impact of interconnected risk sources, on the efficiency of manufacturing companies. The proposed framework utilises a novel mixed-integer linear programming (MILP) model to minimize the time of satisfying the orders while it considers the risk associated with suppliers and manufacturers. The MILP model considers the relationships among (i) material and suppliers and (ii) work centers to measure the propagation of risks throughout the production system. The proposed framework also utilises the Monte Carlo simulation to calculate the associated likelihood of delay and the distribution of the delivery time of orders. To show the complication of the propagation of risk, two distinct scenarios are compared. The first scenario considers zero risks, while the second one assigns probabilistic risk to the suppliers and work centers. The results highlight the magnitude and the complexity of the risk propagation from various interconnected sources through the production system. It also identifies the most vulnerable components of the production system affected more by various types of risk.

关键词： Risk assessment resilient supply chain production planning mixed-integer linear programming Monte Carlo simulation

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Market Power-Constrained Transmission Expansion Planning Using Bi-Level Optimization

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2023年第1期19卷 113-124页

作者： El-Meligy, Mohammed A. El-Sherbeeny, Ahmed M. Mahmoud, Haitham A. King Saud Univ Coll Engn Ind Engn Dept POB 800 Riyadh 11421 Saudi Arabia

Market power evaluation must be a primary concern when deciding to expand a transmission network in a restructured electricity grid since a well-designated transmission network can effectively mitigate market power. In this regard, a scenario-driven transmission expansion planning model is proposed to find the least-cost solution for optimal transmission grid configuration considering market power in the electricity market. The presented methodology is formulated as a stochastic bi-level optimization problem. The upper level identifies the optimal expansion plan and generation output under uncertainty in renewable energy sources and electric demand. Given the optimal expansion strategy obtained from the upper level, the lower level computes the expanded power system's transmission-constrained structural market power measure. Within this bi-level framework, the planner can mitigate market power exerted by generation units to avoid consumer overpayment. The Karush-Kuhn-Tucker conditions are used to form a mixed-integer linear programming problem, which can be effectively solved by branch-and-cut solvers. The modified IEEE 118-bus power system is used to corroborate the effectiveness of the bi-level structure of the market power-constrained transmission expansion planning model.

关键词： Bi-level programming Karush-Kuhn-Tucker conditions Market power mixed-integer linear programming Stochastic optimization Transmission expansion planning

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On the MILP Modeling of Remote-Controlled Switch and Field Circuit Breaker Malfunctions in Distribution System Switch Placement

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IEEE ACCESS 2023年 11卷 40905-40915页

作者： Jooshaki, Mohammad Karimi-Arpanahi, Sahand Millar, R. John Lehtonen, Matti Fotuhi-Firuzabad, Mahmud Geologian Tutkimuskeskus GTK Circular Econ Solut Unit Espoo 02151 Finland Univ Adelaide Sch Elect & Mech Engn Adelaide SA 5005 Australia CSIRO Energy Newcastle NSW 2304 Australia Aalto Univ Dept Elect Engn & Automat Espoo 02150 Finland Sharif Univ Technol Dept Elect Engn Tehran 113658639 Iran

Installing sectionalizing switches and field circuit breakers (FCBs) is vital for the fast restoration of customer electricity supply in distribution systems. However, the high capital costs of these protection devices, especially remote-controlled switches (RCSs) and FCBs, necessitate finding a trade-off between their costs and financial benefits. In this study, we propose a mixed-integer linear programming (MILP) model for optimizing switch planning in distribution systems. The proposed model determines the optimal allocation of manual switches, RCSs, and FCBs to minimize the costs of switches and the reliability-oriented expenses. While the former includes the costs of installing and operating the switches, the latter consists of the distribution company's lost revenue due to the undelivered energy and the regulatory incentives (or penalties) associated with service reliability indices. Two penalty-reward mechanisms are used to account for the financial benefits of increasing the service reliability through reducing the duration and frequency of interruptions. Proposing a novel reliability assessment model, we consider the possibility of malfunctions in both RCSs and FCBs in a highly efficient manner, which is a major contribution of this work. The proposed MILP model is applied to three test networks to validate its applicability and efficacy. The results show the importance of considering the possibility of switch malfunctions in distribution networks.

关键词： Reliability Switches linear programming Costs Load modeling Distribution networks Circuit breakers Distribution system reliability field circuit breaker mixed-integer linear programming optimal switch placement remote-controlled switch

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Integrated planning decisions in the broiler chicken supply chain

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2023年第4期30卷 1931-1954页

作者： Solano-Blanco, Alfaima L. Gonzalez, Jaime E. Gomez-Rueda, Luis O. Vargas-Sanchez, Jhon J. Medaglia, Andres L. Univ Los Andes Ctr Optimizac & Probabilidad Aplicada COPA Dept Ingn Ind Cra 1 Este 19A 40 Bogota DC Colombia Polytech Montreal Dept Math & Ind Engn 2900 Blvd Edouard Montpetit Montreal PQ H3T 1J4 Canada Univ Los Andes Dept Ingn Ind Prod & Logist PyLO Cra 1 Este19A-40 Bogota DC Colombia Univ Magdalena Dept Ingn Ind Estadist & Metodos Cuantitat Carrera 3222-08 Santa Marta Dtch Colombia

In the poultry industry, the meat market requires a careful coordination of the broiler chicken supply chain comprising breeders, hatcheries, farms, slaughterhouses, wholesale, and retail vendors. Aside from the inherent challenges of coordinating a supply chain, animal husbandry systems face additional complex tasks. The lack of integrated decisions within the poultry chain could lead to a production plan that (a) does not comply with the biosecurity standards required in meat production for human consumption at the farms;(b) violates the production and inventory capacities at the slaughterhouses;and (c) does not meet the demand of customers. To streamline the supply chain, we propose a mixed-integer linear programming model that supports production planning and scheduling decisions in broiler chicken production facilities. In addition, we embedded the mixed-integer programming model in a rolling-horizon scheme to improve scalability and to avoid the myopic effect of time-indexed optimization models that put too much emphasis on a specific time period. We present the results of a case study in a poultry company in Santa Marta (Colombia), where we reach profit improvements that range from 7% to 57% with a reduction in inventory costs that range from 30% to 60%, while simultaneously meeting stringent technical, tactical, and biosecurity constraints.

关键词： poultry supply chain mixed-integer linear programming production planning lot-sizing decisions decision support system rolling horizon

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Materializing International Trade of Decarbonized Hydrogen Through Optimization in Both Economic and Environmental Aspects

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ACS SUSTAINABLE CHEMISTRY & ENGINEERING 2023年第1期11卷 155-167页

作者： Kim, Ayeon Kim, Heehyang Lim, Dongjun Cheon, Seunghyun Lim, Hankwon Ulsan Natl Inst Sci & Technol Sch Energy & Chem Engn Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol Grad Sch Carbon Neutral Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol Carbon Neutral Demonstrat & Res Ctr Ulsan 44919 South Korea

As deviations in H-2 production capacity by countries become a considerable barrier to the realization of the global H-2 economy, international trade between countries with abundant resources and those with limited resources is required. In line with this trend, numerous supply chains between several countries have been planned, and associated studies have been conducted. However, the study which treats international overseas H-2 trade chains considering numerous major importing and exporting countries has rarely been conducted before. In this study, a comprehensive optimization for the overseas H-2 supply chain considering the three major importing countries including Korea, Japan, and Germany was conducted with mixed-integer linear programming considering both economic and environmental aspects simultaneously. Through the optimization study, the most feasible H-2 supply chains for each importing country could be verified according to years and case scenarios. Blue H-2 from Qatar turns out to be the most feasible supply chain for Japan in 2030, while green H-2 from South Africa is the most feasible one for other importing countries. In 2040, green H-2 from South Africa and Australia becomes the best one for Asian importers, and Australia finally dominates all the supplies after 2050. In the case of Germany, green H-2 from Spain is considered the best after 2040. Depending on the scenario, the difference in the selected countries and supply amounts is not significant, though the costs are varied. Ammonia turns out to be the most feasible carrier for H-2, and the total cost including the carbon tax ranges from 2.15 to 3.43 $ kgH(2)(-1), which is a range from the current green H-2 to the blue H-2 price.

关键词： overseas H-2 supply chain economic analysis carbon footprint analysis carbon tax mixed-integer linear programming case scenario analysis

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Constrained Assortment Optimization Under the Cross-Nested Logit Model

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PRODUCTION AND OPERATIONS MANAGEMENT 2024年第10期33卷 2073-2090页

作者： Le, Cuong Mai, Tien Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore

We study the assortment optimization problem under general linear constraints, where the customer choice behavior is captured by the cross-nested logit model. In this problem, there is a set of products organized into multiple subsets (or nests), where each product can belong to more than one nest. The aim is to find an assortment to offer to customers so that the expected revenue is maximized. We show that, under the cross-nested logit model, the unconstrained assortment problem is NP-hard even when there are only two nests, and the problem is generally NP-hard to approximate to any constant factors. To tackle this challenging problem, we develop a new discretization mechanism to approximate the problem by a linear fractional program with a performance guarantee of ( 1 - & varepsilon;) / ( 1 + & varepsilon;) , for any accuracy level & varepsilon;> 0 . We then show that optimal solutions to the approximate problem can be obtained by solving mixed-integer linear programs. We further show that our discretization approach can also be applied to solve a joint assortment optimization and pricing problem, as well as an assortment problem under a mixture of cross-nested logit models to account for multiple classes of customers. Our empirical results on a large number of randomly generated test instances demonstrate that, under a performance guarantee of 90% (i.e., expected revenues are guaranteed to be at least 90% of the optimal revenue), the percentage gaps between the objective values obtained from our approximation methods and the optimal expected revenues are no larger than 1.2%.

关键词： Constrained assortment optimization cross-nested logit discretization mixed-integer linear programming

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Integrated Approaches in Resilient Hierarchical Load Forecasting via TCN and Optimal Valley Filling Based Demand Response Application

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APPLIED ENERGY 2024年 360卷

作者： Tuerkoglu, A. Selim Erkmen, Burcu Eren, Yavuz Erdinc, Ozan Kuecuekdemiral, Ibrahim Yildiz Tech Univ Dept Elect Engn TR-34220 Istanbul Turkiye Yildiz Tech Univ Dept Elect & Commun Engn TR-34220 Istanbul Turkiye Yildiz Tech Univ Dept Control & Automat Engn TR-34220 Istanbul Turkiye Glasgow Caledonian Univ Sch Comp Engn & Built Environm Dept Appl Sci Glasgow G4 0BA Scotland

Considering the electricity market, data analytics paves the way for completely new strategies regarding demand and supply-side policies. In this manner, predictive analysis of the demanded power accuracy is carried out to boost profits and increase the penetration of similar demand response (DR) programs across all levels of end -user categories. Residential loads experience stiff spikes and unpredictable variations due to occupancy activities and environmental factors. To address this, we first propose a robust short-term multivariate -multistep forecasting framework that is resilient to missing or erroneous data, employing temporal convolution networks (TCNs). We then incorporate two distinct valley -filling indices to optimize the charging of electric vehicle loads according to DR requirements, showcasing the efficacy of leveraging artificial intelligence to enhance the utilization of clean energy resources. Simulation studies are conducted using real -world nodal residential loads with hourly granularity. The results demonstrate that the forecasting method is reliable for residential locations, even when dealing with highly damaged data. The case studies effectively fill the load into the valleys and minimize fluctuations in residential locations. Through the integration of emission -aware forecasting and optimization strategies, our study lays the groundwork for a comprehensive approach that not only improves economic outcomes and grid stability but also advances the imperative of reducing carbon emissions.

关键词： Demand response Electric vehicle Hierarchical load forecasting mixed-integer linear programming Temporal convolutional networks

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Towards energy transition: A novel day-ahead operation scheduling strategy for demand response and hybrid energy storage systems in smart grid

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ENERGY 2024年 293卷

作者： Elsir, Mohamed Al-Sumaiti, Ameena Saad Moursi, Mohamed Shawky El Khalifa Univ Adv Power & Energy Ctr Elect Engn & Comp Sci Dept Abu Dhabi U Arab Emirates

Fossil fuel power plants continue to contribute significantly to carbon emissions, necessitating a transition towards cleaner energy sources. Despite the growing presence of renewables within the power systems, the incorporation of carbon capture technologies into the traditional thermal power plants holds great potential in emissions reduction. In this paper, the integration of renewable energy sources (RES) and coal-fired power generation units outfitted with carbon capture schemes is addressed. Multiple demand response (DR) programs and hydropower plants are strategically utilized to increase the power system flexibility. To effectively plan the day-ahead (DA) operation of the power system, a presumed market-clearing framework is adopted and modelled as a risk-constrained two-objective stochastic mixed-integer linear programming problem. The proposed framework helps to tackle the uncertainties related to RES and demand variations by employing a hidden Markovian process (HMP) technique. To simultaneously minimize the system's operational costs and CO2 emissions, an enhanced version of the augmented..-constraint method is employed. To prove its value, the proposed framework is devoted to the 24-bus IEEE reliability test system (IEEE-RTS). The system features substantial penetration of RES (exceeding 87% of peak load) and standard DR options capacities (less than 25% of peak load). The results show a 24% reduction in load peaks, an over 63% decrease in emissions, and a 17% reduction in the overall operation costs.

关键词： Energy transition Demand response Network-constrained unit commitment Hidden Markovian process Risk-constrained two-objective stochastic mixed-integer linear programming

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Single machine scheduling with release dates: A distributionally robust approach

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期308卷 19-37页

作者： Lu, Haimin Pei, Zhi Zhejiang Univ Technol Coll Mech Engn Hangzhou 310023 Peoples R China

In the present study, a single machine scheduling problem with job release dates is considered, where the job processing time is depicted by an ambiguity set, with the mean, the mean absolute deviation, and the support set information given. To the best of our knowledge, this is the first time that a distribution -ally robust optimization method is applied to the single machine scheduling with release dates. Based on the risk attitude of the decision maker, two distributionally robust optimization models are proposed, namely, the risk-neutral and risk-averse scheduling. The two models concern with the worst-case per-formance and the robust conditional value-at-risk with respect to the total flow time, respectively. Since the proposed robust optimization models are intractable in nature, we reformulate them as two separate mixed-integer linear programming models, which can then be solved via off-the-shelf solvers. Interest-ingly, it is proved that the mean absolute deviation can be ignored in the risk-neutral robust model. Thus a more succinct reformulation is constructed, which can be rapidly solved to optimum. Furthermore, ex-tensive numerical experiments are performed with the stochastic programming model as a benchmark. And it is observed that the risk-averse model outperforms the others on both the average and worst-case metrics in most cases. Meanwhile, the risk-neutral model is more preferable on the average metric when the jobs are sparsely released.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Scheduling Release date Distributionally robust optimization CVaR mixed-integer linear programming

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