This paper focuses on the environmental and economic impact of electric railway systems (ERS) and introduces Railway Energy Management Systems (REMS) as a green solution to reduce greenhouse gas (GHG) emissions and CO...
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ISBN:
(纸本)9798350386509;9798350386493
This paper focuses on the environmental and economic impact of electric railway systems (ERS) and introduces Railway Energy Management Systems (REMS) as a green solution to reduce greenhouse gas (GHG) emissions and CO2 pollution and reducing the operational cost of the station while allowing surplus electricity sales to the grid market. The research utilizes mixedintegerlinearprogramming (MILP) to optimize the operation cost and GHG reduction of railway station electrical systems in Milan, Italy. The study considers Renewable Energy Resources (RERs), Energy Storage Systems (ESSs), Regenerative Braking Energy (RBE), and the electrical grid. It also incorporates real-time data to account for the probabilistic and stochastic behaviors of these elements, leading to a significant cost reduction of 56.09% in smart railway station operations. MATLAB is employed to solve the model effectively, demonstrating the suitability and effectiveness of the proposed approach with compelling evidence of operational cost and GHG reductions in various scenarios, achieving a reduction of 3458.26 kg/day in the best scenario.
Background: To lower environmental impact of human food consumption, replacement of animal proteins with plant-based proteins is encouraged. However, the lower iron bioavailability of plant-based foods is rarely consi...
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Background: To lower environmental impact of human food consumption, replacement of animal proteins with plant-based proteins is encouraged. However, the lower iron bioavailability of plant-based foods is rarely considered when designing healthy and sustainable diets by using diet modeling. The estimated absorbable iron content of vegetarian and vegan menu plans might therefore be too ***: The main aim of this study was to investigate and compare the impact of various methods to estimate absorbable iron intake on the nutritional adequacy of omnivorous, vegetarian, and vegan menu plans designed for women of reproductive age. Methods: A diet model was developed to design menu plans consisting of a selection of meals that best complied with nutritional re-quirements. Meals used for modeling were created based on food intake data from the National Health and Nutrition Examination Survey (NHANES). For each meal, absorbable iron concentrations were estimated by using 2 constant absorption factors (18% and 10%) and 2 diet-dependent absorption equations (Conway and Hallberg). For each absorption method and diet type, we used the diet model to design the optimal menu plan. Retrospectively, menu plans were evaluated by estimating the absorbable iron content by using the other absorption methods. Results: Retrospective diet-dependent absorbable iron estimates were consistently lower than estimates based on constant absorption factors. Using diet-dependent estimates increased absorbable iron by optimizing enhancer and inhibitor ***: Iron bioavailability should be considered when modeling diets.
Background: Controlled feeding trials are an important method to determine cause-effect relationships between dietary intake and metabolic parameters, risk factors, or health outcomes. Participants of a controlled fee...
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Background: Controlled feeding trials are an important method to determine cause-effect relationships between dietary intake and metabolic parameters, risk factors, or health outcomes. Participants of a controlled feeding trial receive full-day menus during a prespecified period of time. The menus have to comply with the nutritional and operational standards of the trial. Levels of nutrients under investigation should differ sufficiently between intervention groups, and be as similar as possible for all energy levels within intervention groups. Levels of other key nutrients should be as similar as possible for all participants. All menus have to be varied and manageable. Designing these menus is both a nutritional and a computational challenge that relies largely on the expertise of the research dietician. The process is very time consuming, and last-minute disruptions are very hard to ***: This paper demonstrates a mixedintegerlinearprogramming model to support the design of menus for controlled feeding ***: The model is demonstrated for a trial that involved consumption of individualized, isoenergetic menus with either a low or a high protein ***: All menus generated by the model comply with all standards of the trial. The model allows for including tight ranges on nutrient composition, and complex design features. The model is very helpful in managing contrast and similarity of key nutrient intake levels between groups and energy levels, and in coping with many energy levels and nutrients. The model helps to propose several alternative menus and to manage last-minute disruptions. The model is flexible;it can easily be adapted to suit trials with other components or different nutritional ***: The model helps to design menus in a fast, objective, transparent, and reproducible way. It greatly facilitates the design procedure for menus in controlled feeding trials and lowers development costs.
In this study, machine scheduling with variable capacity over time (SVCap) is investigated. The machine capacity is the maximum number of jobs that a machine can process at a time which can be either fixed or variable...
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In this study, machine scheduling with variable capacity over time (SVCap) is investigated. The machine capacity is the maximum number of jobs that a machine can process at a time which can be either fixed or variable over time. In common machine scheduling problems, it is assumed that one machine can process one job at a time. However, in variable machine capacity, multiple jobs can be processed on a machine simultaneously. Unlike the current research, a mathematical formulation is not developed yet for solving this problem. In order to solve the problem, a novel mixedintegerlinearprogramming (MILP) is proposed. In addition, the SVCap is regarded as a special type of resource-constrained project scheduling problem (RCPSP). Thus, the discrete-time (DT) formulation is generalized to solve the SVCap. In these formulations, the total tardiness is minimized as the objective function. Proposed models are implemented on an irrigation scheduling problem in which water resources are allocated to each plot of farmland. The computational performances of proposed formulations are evaluated on problem instances with different sizes. Results show that the proposed formulations solved all problem instances. The results demonstrate that the proposed MILP formulation is more efficient than the generalized DT formulation in both solution quality and runtimes.
In this work, we address a nationwide tactical planning for industrial gas supply chains, particularly argon. The proposed approaches follow as extensions of our previous work (Comp. & Chem. Eng., 161 (2022) 10777...
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In this work, we address a nationwide tactical planning for industrial gas supply chains, particularly argon. The proposed approaches follow as extensions of our previous work (Comp. & Chem. Eng., 161 (2022) 107778) in which a regional argon supply chain problem is addressed;in that work, both production and distribution could be represented in detail. Two different types of deliveries from the Air Separating Units (ASU) to customers, which involve single driver deliveries for short distance trips and sleeper team that require multiple days. The nationwide problem requires simplifications to keep the problem mathematically tractable, primarily the representation of production sites with different tier costs and the aggregation of customers in clusters. The regional problem addressed in our previous work is used as a benchmark case study for benchmarking. We then focus on a real-world problem that represents a nationwide argon supply chain. Despite the size of the models, near optimal solutions could be found in reasonable times. Finally, we highlight important features of the proposed approaches.
The design and development of renewable energy resources-based poly-generation microgrids have recently increased to supply multiple demands such as cool, heat, and power as well as mitigate pollutants improving effic...
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The design and development of renewable energy resources-based poly-generation microgrids have recently increased to supply multiple demands such as cool, heat, and power as well as mitigate pollutants improving efficiency. This paper aims to develop a combined cooling, heating, and power production network integrating photovoltaic panels (PVs), wind and gas turbines, a battery, an ice bank tank, a heater, an electrical chiller, a thermal energy storage medium. In this tri-generation facility, natural gas is utilized for district heating and fueling the gas turbine power generation cycle. The local power distribution system in combination with the output powers of PVs, wind and gas turbines is used to directly supply the electrical appliances, ice maker process, and chiller as well as charge the battery storage unit. Moreover, the air/water-cooled chiller procures the cooling flux for a benchmark microgrid. Its heating energy requirement is also provided by the gas-fired heater, the flue gases of the gas turbine, and the thermal storage medium. A mixedintegerlinearprogramming problem is coded using a generalized algebraic modeling system (GAMS) to minimize daily operating costs and emissions. Simulations are examined and analyzed over a 24-h study horizon on a sample summer day. Time-of-use energy rates and RTPs are considered two strategic demand response schemes to investigate the cost-effectiveness capability of the gas-power nexus model. The proposed approach is coded using a GAMS to confirm its effectiveness and cost-environ benefits in four cases with and without heat/cool/electrical storage units considering time-of-use energy rates and real-time prices.
With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range a...
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With large-scale electric vehicles (EVs) promoted and connected to the power grid, the uncontrolled charging of EVs enlarges the peak-valley range of load in the distribution grid. To alleviate the peak-valley range and enhance the stability of the distribution grid, vehicle-grid integration (VGI) is proposed as an economic and potential solution. However, the impact of disorderly charging and the potential of VGI considering random user behavior requires clarification. This paper established a mixed-integer linear programming model with user behavior simulated by the Monte Carlo algorithm. The travel and charging behavior of EVs are provided by Monte Carlo simulation with characteristic parameters from statistical data of urban vehicle travel data. A digital model describing the VGI charging boundary is built to restrict the transition from uncontrolled charging to VGI. Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. This study clearly demonstrates the effectiveness of VGI and guides the implementation of VGI in the rapid growth of EVs.
The paper presents the structure of an open-source software tool that can solve an Optimal Network Reconfiguration problem for a distribution grid. The problem includes kinship constraints that permit to fully represe...
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ISBN:
(纸本)9798350378498;9788887237627
The paper presents the structure of an open-source software tool that can solve an Optimal Network Reconfiguration problem for a distribution grid. The problem includes kinship constraints that permit to fully represent the logics which are behind the principal distribution automation schemes adopted by Distributor System Operators to deal with the fault detection, isolation and recovery function. The algorithm is structured to be fully open-source and it is developed on a Python-based environment. The adopted network models are also open-source and based on the Open-DSS software. Results obtained on the model of a realistically sized MV primary distribution network are shown.
This research is dedicated to formulating a practical problem related to the assignment of oncology clinic routes. The objective is to schedule medical events for patients attending health centers, taking into account...
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ISBN:
(纸本)9798350373981;9798350373974
This research is dedicated to formulating a practical problem related to the assignment of oncology clinic routes. The objective is to schedule medical events for patients attending health centers, taking into account the variable demand and limited resources in this field. To achieve this, three types of solutions are considered. The first is an Online Scheduling Algorithm, which simulates a scheduling process based on medical routes and also includes its inverse version. The next is a mixed-integer linear programming (MILP) model. In this case, information is centralized, and patients are scheduled based on their requirements, minimizing delays in their appointments and/or medical treatments. These methodologies are compared with the current mode of assignment used. To test the previously proposed solutions, data provided by the Arturo Lopez Perez Foundation (FALP) will be used.
This paper addresses freight consolidation in rail transportation planning. Multiple demand destinations are served in a single trip to utilise the volume discount on freight rate. An efficient mixed-integerlinear pr...
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This paper addresses freight consolidation in rail transportation planning. Multiple demand destinations are served in a single trip to utilise the volume discount on freight rate. An efficient mixed-integer linear programming (MILP) based modelling framework is proposed to optimally allocate rail wagons to a given set of destinations considering the shipment options offered by Indian Railways. Twelve problem instances are derived using real data from an Indian food grain organisation and are solved to optimum using the CPLEX solver in quick time. The results indicate that multi-point orders can reduce the total transportation cost and ease the handling of shipments at terminals. (c) 2025 Published by Elsevier Ltd on behalf of Indian Institute of Management Bangalore. This is an open access article under the CC BY-NC-ND license (http://***/licenses/ by-nc-nd/4.0/)
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