Managers of mobile photo enforcement (MPE) programs must account for several road safety goals when deploying operators. However, there is no MPE design structure to systematically connect deployment decisions back to...
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Managers of mobile photo enforcement (MPE) programs must account for several road safety goals when deploying operators. However, there is no MPE design structure to systematically connect deployment decisions back to preset goals. We propose a method to aid MPE managers in using goals directly in the efficient allocation of limited program resources. A neighborhood-level resource allocation model is developed, which uses multi-objective optimization to determine how enforcement is allocated to city neighborhoods. The model is applied to an MPE program in Edmonton, Alberta, Canada, and delivered 200 optimal solutions for one month. One illustrative solution is plotted in GIS and assessed alongside the actual program deployment results for the same month. This solution efficiently allocates one month of operator shifts to sites in 44 neighborhoods, based on the specific needs of each neighborhood. The actual MPE deployment was such that 60% of visits occurred in neighborhoods beyond the 44 identified in the illustrative optimal solution. The major contribution of our model is that it allows for MPE managers to quantitatively map performance outcomes to multiple program goals. This can lead to more transparent and efficient MPE programs, which in turn can improve urban road safety and ultimately, urban sustainability.
This paper presents AUGMECON-Py, a Python framework for solving large and complex multi-objective linear programming problems under uncertainty, optimally and robustly capturing all solutions. On the core of the AUGME...
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This paper presents AUGMECON-Py, a Python framework for solving large and complex multi-objective linear programming problems under uncertainty, optimally and robustly capturing all solutions. On the core of the AUGMECON-Py software lies the integration of a well-established optimisation algorithm (AUGMECON) with Monte Carlo analysis that helps maximise robustness against stochastic uncertainty, thereby avoiding the complexity of numerous cascading methods and code scripts. Using an object-oriented language, AUGMECON-Py overcomes limitations of its predecessors regarding memory requirements, and further extends the solution algorithm to ensure no efficient solution is left outside the solution grid. The framework is easily accessible, offering effortless data pre-and post-processing, management, and visualisation of results.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
This paper presents a cooperative production planning method. The method is mainly based on a horizontal decomposition, every department of the plant cooperates in order to obtain a good global plan. Coordination is m...
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This paper presents a cooperative production planning method. The method is mainly based on a horizontal decomposition, every department of the plant cooperates in order to obtain a good global plan. Coordination is made by the plant managers. The departments will solve multi-objective linear programming problems. In this process a large number of goals is under attention, including goals expressed by expert knowledge. A production plan with high quality technical and economic features can be very fast constructed in order to extend through worldwide the processing business of petrochemical plants
This study assesses the contribution of the implementation of the Calcium Looping (CaL) process to capture carbon dioxide (CO2) from coal power plants in Brazil, as a strategy to meet the established environmental goa...
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This study assesses the contribution of the implementation of the Calcium Looping (CaL) process to capture carbon dioxide (CO2) from coal power plants in Brazil, as a strategy to meet the established environmental goals for 2030. A multi-objective linear programming model based on Input-Output analysis (IO-MOLP) is developed to evaluate the interrelations of economic, energy and environmental systems. Three objective functions are considered: maximization of Gross Domestic Product (GDP), minimization of Greenhouse Gas emissions (GHG), and minimization of energy consumption for exclusively energy purposes (CFE). Two scenarios are analyzed: (i) a baseline scenario (BL) which does not incorporate CaL in coal power plants, (ii) a scenario (S1) which incorporates CaL systems. In general, the implementation of CaL in coal power plants improves the overall environmental impact;however, in our results, this reduction was not found significant. On the other hand, a contraction in the economic system and an expansion in the consumption of energy resources may be triggered by this strategy. These results reaffirm the importance of assessing the effects of the environmental and energy decisions and policies on the country's economic system, by means of multi-objective models able to unveil the trade-offs at stake between multiple, conflicting and incommensurate evaluation axes of the merits of those policies.
In container loading and unloading operations, container clusters are more suitable for large-scale operation and coupling scheduling of loading and unloading equipment. Taking a container cluster as a work unit, this...
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In container loading and unloading operations, container clusters are more suitable for large-scale operation and coupling scheduling of loading and unloading equipment. Taking a container cluster as a work unit, this study analyzes the multi-vessel large container clusters operation and researches the optimal scheduling strategy of the yard truck. A multi-objective mathematical programming model is developed through the pre-distribution of inbound container clusters and outbound container clusters, where the objectives are to minimize the non-loaded traveling distance and obtain the shortest completion time to finish the loading and unloading of containers in multiple vessels. The modeled problem is analyzed and solved by a heuristic-adaptive genetic algorithm. Fuzzy membership function and Pareto optimal solution are used to transform the multi-objective mathematical model into a single objective. The two methods are compared with results from the multi-objectiveprogramming problem of the model proposed. The result from the experimental case proved that the result of the Pareto optimal solution is better than that of the fuzzy membership function with regard to the problems of minimizing the distance of non-loaded traveling and finding the shortest completion time to finish the loading and unloading of containers in multiple vessels.
Energy plays a key role in the development of nations and provides vital services and means that improve quality of life. Formulation of an energy model will help in the proper allocation of available energy resources...
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Energy plays a key role in the development of nations and provides vital services and means that improve quality of life. Formulation of an energy model will help in the proper allocation of available energy resources. The objective of this paper is to allocate optimally to each end-use a certain amount of energy to be supplied by a given resource in Iran. In this research, the energy allocation process is looked at from three points of view: policy, economy and environment. In this way, energy demands of end-uses are forecasted using neural networks and fuzzy linear regression methods. The outcomes are used in a fuzzy multi-objective linear programming model, which determines the optimum allocation of energy resources of Iran from 2011 to 2020. The results provide scientific basis for the optimal allocation of energy resources in meeting the future energy demand in Iran.
For high-tech companies to consider when purchasing product, product life cycle cost is one of the most important evaluation tools. We develop a new efficient solution product life cycle cost model that addresses ten ...
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For high-tech companies to consider when purchasing product, product life cycle cost is one of the most important evaluation tools. We develop a new efficient solution product life cycle cost model that addresses ten goals such as net cost minimization, rejection minimization, late delivery minimization, and minimization of product life cycle cost subject to three realistic vendor capacities and three budget constraints. The results achieved with the four types of goal programming approaches should be useful for determining vendor quotas in supply chain if the capacity and budget constraints of each vendor are not known with certainty. Moreover, we provide high-tech case study how one can solve the product life cycle cost problem within a single-buyer-multiple-supplier procurement situation. Our study main contribution is managers at high-tech companies can easily apply our model to select their vendors in a fuzzy environment.
As the source of the modern enterprise value chain,purchasing value drives the value updated and added *** on construction supply chain,the origin of the purchasing value was analyzed from three dimensions which consi...
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As the source of the modern enterprise value chain,purchasing value drives the value updated and added *** on construction supply chain,the origin of the purchasing value was analyzed from three dimensions which consist of materials value,suppliers value,and social value in this paper.A multi-objective linear programming model was proposed and solved by the fuzzy *** by the application of the model based on the example of EHDC procurement,the distribution result kept with the purchasing intention of the *** to the traditional purchasing model which was just to control the cost as the core,the order quantities was distributed according to materials value,suppliers value,and social value further in this model.
The scale and distribution of electric multiple unit maintenance base are important to improve the efficiency and capacity of high-speed railway network,but it is less studied in previous *** the basis of studying for...
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The scale and distribution of electric multiple unit maintenance base are important to improve the efficiency and capacity of high-speed railway network,but it is less studied in previous *** the basis of studying foreign experiences of distribution of electric multiple unit maintenance base,and examination and repair method,the paper analyzes the characteristics and affecting factors of maintenance base in *** analytic hierarchy process,a comprehensive evaluation model is established for selecting candidate cities as locations of maintenance *** result is obtained with expert scoring *** the result,a multi-objective linear programming model is constructed for solving the problem of distribution of maintenance *** model is solved with some hypothetical data and some reasonable conclusions are ***,the method for determining the scale and distribution of electric multiple unit maintenance bases is applicable.
A multi-product, multi-period, multi-objective linear programming model has been built as a contribution to good management of a blood donation–transfusion system in order to determine the best assignment of blood re...
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A multi-product, multi-period, multi-objective linear programming model has been built as a contribution to good management of a blood donation–transfusion system in order to determine the best assignment of blood resources to demand, which minimizes the quantity of blood imported from outside the system and stabilizes the quantities assigned daily. The model has been applied to the Italian Red Cross (CRI) blood donation–transfusion system in Rome and to each hospital belonging to such a system, producing interesting results. International Federation of Operational Research Societies 2001.
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