Interior-point methods, particularly the cutting-plane strategy, have emerged as interesting techniques in optimization. The main idea of the cutting-plane method is to cut off parts of the feasible set and shrink it ...
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Interior-point methods, particularly the cutting-plane strategy, have emerged as interesting techniques in optimization. The main idea of the cutting-plane method is to cut off parts of the feasible set and shrink it by removing the points where optimality is surely not attained. The aim of this study is to improve the convergence speed of a newly developed modified cutting-plane method for multi-objective optimization problems. The effectiveness of the proposed approach is emphasized by its ability rapidly to shrink the feasible space, strengthen the optimal solution search method, and at the same time minimize the computational overhead. Additionally, it is demonstrated that the method is capable of achieving well-distributed efficient solutions on the efficient frontier by purposefully assigning weight vectors. The experimental analysis carried out confirms the effectiveness of the suggested method and offers a new promising perspective for addressing multi-objective optimization challenges.
As the issue of global climate change becomes increasingly severe, governments worldwide have implemented carbon reduction policies, such as carbon taxes and industrial low-carbon transitions, to effectively control t...
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As the issue of global climate change becomes increasingly severe, governments worldwide have implemented carbon reduction policies, such as carbon taxes and industrial low-carbon transitions, to effectively control total carbon emissions. This study applies a multi-objective programming approach and uses the plastic raw material manufacturing process in the petrochemical industry as an example to explore how companies can balance profit maximization with minimizing production-related carbon emissions. By integrating Activity-Based Costing (ABC) and the Theory of Constraints (TOC), this study develops a production decision-making model and employs the epsilon-constraint method to impose carbon emission constraints, analyzing the resulting changes in corporate profitability. The model considers three different policy scenarios: basic carbon tax costs (including the use of renewable energy), continuous incremental progressive carbon tax costs, and discontinuous incremental progressive carbon tax costs. The results indicate that adopting renewable energy effectively reduces carbon emissions during production, while the discontinuous incremental carbon tax model provides better control over emissions. Under different carbon emission constraints, significant variations in optimal profits and production volumes are observed across the models, offering valuable insights for governments and enterprises in formulating carbon reduction strategies.
Selection of appropriate suppliers and allocation the orders among them have become the two key strategic decisions regarding purchasing. In this study, a two-phase integrated approach is proposed for solving supplier...
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Selection of appropriate suppliers and allocation the orders among them have become the two key strategic decisions regarding purchasing. In this study, a two-phase integrated approach is proposed for solving supplier selection and order allocation problems. Phase 1 contains four techniques from statistics and Machine Learning (ML), including Auto-Regressive Integrated Moving Average, Random Forest, Gradient Boosting Regression, and Long Short-term Memory for forecasting the demands, using large amounts of real historical data. In Phase 2, suppliers' qualitative weights are determined by a fuzzy logic model. Then, a new multi-objective programming model is designed, considering multiple periods and products. In this phase, the results of Phase 1 and the results of the fuzzy model are utilized as inputs for the multi-objective model. The weighted-sum method is applied for solving the multi-objective model. The results show Random Forest model leads to more accurate predictions than the other examined models in this study. In addition, based on the results, the selection of the forecasting techniques and different weights of suppliers affect both supplier selection and the related orders.
Water shortages and supply pressures due to the special geographical environment pose significant challenges to the social and economic development of the Minjiang River Basin in Fujian Province, China. This study int...
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Water shortages and supply pressures due to the special geographical environment pose significant challenges to the social and economic development of the Minjiang River Basin in Fujian Province, China. This study introduced a semi-infinite interval type-2 fuzzy multi-objective programming (SIIT2F-MOP) model to optimize the water resource system under conditions of uncertainty. Additionally, a novel multi-criteria decision analysis (MCDA) method, integrating the interval-based technique for order of preference by similarity to ideal solution (ITOPSIS), was developed to analyze and evaluate water allocation results using interval data instead of specific values. The SIIT2F-MOP model combines semi-infinite programming, multi-objective optimization, and interval type-2 fuzzy sets to address uncertainties and resolve conflicts among multiple decision-makers in water resource management. The innovations and contributions of this study are as follows: (i) prioritizing the restructuring of secondary industries while advancing manufacturing and modern service sectors can promote economic development and mitigate water shortages, and net system benefits increased by 7.2 %;(ii) evaluation of water allocation options using the ITOPSIS method demonstrates that industrial benefits account for 53.8 % of the optimal scenario;and (iii) the proposed model facilitates dynamic analysis of economic efficiency, equity in water distribution, and water scarcity within the water resource system. By integrating advanced optimization and decision-making techniques, this study contributes to sustainable resource management and supports risk control in the face of growing water demand.
Balancing the tradeoff between economy, energy, environment, water resources and carbon emissions has become the major challenge for sustainable development. In this study, a fuzzy multi-objective method is developed ...
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Balancing the tradeoff between economy, energy, environment, water resources and carbon emissions has become the major challenge for sustainable development. In this study, a fuzzy multi-objective method is developed by integrating multi-objective programming, fuzzy linear programming and multiple scenarios. The developed approach can tackle multiple uncertainties and complexities existing in economy-energy-environment system, random carbon dioxide emission and water consumption control policies mix. Results disclose that (1) policy orientation and carbon emission control policy can achieve both carbon and water resource control goals, and water resource control policies are relatively unnecessary;(2) the tertiary sector will become the leading industry, accounting for more than three quarters of the total output value, the construction industry will also overgrow, and the proportion of the manufacturing industry will drop significantly;(3) coal still dominates in the energy production and total quantity consumed, and petroleum consumption will fall, coal accounts for about 75 percent of total energy consumption and electricity for about 15 percent;(4) according to different sources, carbon dioxide emissions are mainly from coal and electricity utilization. Coal's contribution gradually rose to 65 percent, while electricity dropped from 35 percent to 30 percent. For each industry, the mining industry, the electricity industry and the tertiary sector are the primary sources. (5) the sulfur dioxide control policy and carbon dioxide control policy has a strong correlation, and nitrogen oxide control policies have a specific correlation with them. The water resource control policy and particulate matter control policy are relatively independent. (C) 2022 Published by Elsevier Ltd.
To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is ***...
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To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is *** the interests of passengers and the airport,the model minimizes the total flight delay,the total passengers′walking distance and the number of flights reassigned to other gates different from the planned *** to the characteristics of the gate reassignment,the model is *** the multi-objective programming model is hard to reach the optimal solutions simultaneously,a threshold of satisfactory solutions of the model is *** a simulated annealing algorithm is designed for the *** studies show that the model decreases the total flight delay to the satisfactory solutions,and minimizes the total passengers′walking *** least change of planned assignment is also *** results achieve the goals of disruption ***,the model is verified to be effective.
Active distribution networks have the capability to allow the distributed energy resources integration at reasonable costs, opening new business opportunities. Although the sharing of responsibility among the system s...
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ISBN:
(纸本)9781424483570
Active distribution networks have the capability to allow the distributed energy resources integration at reasonable costs, opening new business opportunities. Although the sharing of responsibility among the system stakeholders (e.g., the Civil Society, the DSO and DER owners) is essential, undeniably they pursue different, and sometimes opposite goals. The authors, by adopting multiobjectiveprogramming to simulate the behavior of the stakeholders, aim at assessing how the system players will drive the distribution evolution under the influence of different regulatory environments. All the scenarios have been analyzed on a case study representative of a typical distribution system. The results presented can help Regulators to define a fairer asset and performance based distribution revenue.
Distributed power access has a significant impact on economy and security of incremental distribution network. In this paper, economy and security are taken as the optimization goal, the constraints such as power bala...
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ISBN:
(纸本)9781728132990
Distributed power access has a significant impact on economy and security of incremental distribution network. In this paper, economy and security are taken as the optimization goal, the constraints such as power balance and voltage deviation are constructed, and the multi-objective programming model of distributed power supply access capacity is established considering the different output scenarios of distributed power supply, and the Pareto optimal solution set is obtained by using non-dominant sequencing genetic algorithm. The validity of the proposed method is verified based on the analysis of the IEEE33 node model.
As the elevator group control system of airport logistics has the characteristics of multi-objective, non-linearity, uncertainty, disturbances and incomplete information and so on, to improve the service quality and o...
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ISBN:
(纸本)9783037859520
As the elevator group control system of airport logistics has the characteristics of multi-objective, non-linearity, uncertainty, disturbances and incomplete information and so on, to improve the service quality and operational efficiency of elevator group control system, we created a more comprehensive performance evaluation index function. We used the algorithm called multi-objective optimization, which can reduce the time passengers waiting for the ladder, avoid crowding, and use less energy. According to different demands, select different optimal combination, to meet passengers' demands as possible as we can. With the use of computer simulation technology, we obtained the simulation results, and proof the feasibility and superiority of this algorithm.
According to Hainan Island's biological characteristics, and existing structure of productivity of tropical crops and local climatic conditions, this paper carries on regional division of tropical crops by fuzzy m...
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According to Hainan Island's biological characteristics, and existing structure of productivity of tropical crops and local climatic conditions, this paper carries on regional division of tropical crops by fuzzy mathematics. Based on calculation of basic parameters for tl1e formation of production, near-tem optimum models of tropical crops structure of each region was established by means of multi-objective programming, and a far-term grey programming model was set up through the above-mentioned near-term model and prediction of future parameters. Conclusion shows that the near-term programming may raise the profit by 5. 1-55.7 percent and far-tem programming by 54-90 percent, both gainingobvious economic benefits.
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