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multi-objective programming for economy-energy-environment system and policy mix with dual constraints of carbon emission and water consumption based on multi-scenario analysis

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ENERGY REPORTS 2022年 8卷 7884-7891页

作者： Fu Zhenghui Zhang Yang He Shanshan Wang Han Jiang Xia Wang Shuhang Chinese Res Inst Environm Sci State Environm Protect Key Lab Lake Pollut Contro Natl Engn Lab Lake Pollut Control & Ecol Restorat Beijing 100012 Peoples R China Peking Univ Coll Environm Sci & Engn Beijing 100871 Peoples R China Sino Japan Friendship Ctr Environm Protect Beijing 100029 Peoples R China Chinese Res Inst Environm Sci State Key Lab Environm Criteria & Risk Assessment Beijing 100012 Peoples R China

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.

关键词： multi-objective programming Economy-energy-environment system Carbon dioxide emission Water resource Uncertainty

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UNCERTAIN multi-objective programming MODEL OF TOURIST ROUTE CONSIDERING TOURIST PREFERENCE

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2024年第8期20卷 2640-2651页

作者： Huang, Zheng Ning, Yufu Liu, Fengming Shandong Normal Univ Business Sch Jinan Peoples R China Shandong Youth Univ Polit Sci Sch Informat Engn Jinan Peoples R China Univ Shandong Smart Healthcare Big Data Engn & Ubiquitous Comp C Jinan Peoples R China

. Tourists going out for a trip encounter various uncertainties, such as weather conditions, road conditions, the tourists' consumption budget, travel time, and other uncertainties. Tourists focus on the goals of minimizing travel time and consumption costs while maximizing personal satisfaction with the route;therefore, the multi-objective programming model for an uncertain tourism route problem is established based on uncertainty theory. The objectives of the model are to minimize the travel time and consumption cost and to maximize the tourists' satisfaction with the route. According to inverse uncertainty distribution, the model can be transformed into a traditional programming model and solved by the ant colony algorithm (ACO). Finally, in order to solve the uncertain tourism route programming problem, a numerical example is given to show the application of the model.

关键词： Tourist route programming multi-objective programming uncertainty theory preference

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Using the descent direction in a method of centres algorithm for solving multi-objective programming problems

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ENGINEERING OPTIMIZATION 2025年

作者： Dehmiry, A. H. Yaghoobi, M. A. Vali E Asr Univ Rafsanjan Dept Math Rafsanjan Iran Shahid Bahonar Univ Kerman Dept Appl Math Kerman Iran

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.

关键词： multi-objective programming cutting-plane method method of centres weighted analytic centre

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Research on multi-objective programming Model of Profits and Carbon Emission Reduction in Manufacturing Industry

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ENERGIES 2025年第6期18卷 1411-1411页

作者： Tsai, Wen-Hsien Wu, Yi-Han Natl Cent Univ Dept Business Adm Taoyuan 320 Taiwan

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.

关键词： multi-objective programming epsilon-constraint method carbon emissions carbon tax activity-based costing (ABC) theory of constraints petrochemical industry

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Aubin property for solution set in multi-objective programming

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JOURNAL OF GLOBAL OPTIMIZATION 2023年第2期85卷 441-460页

作者： Rahimi, Morteza Soleimani-damaneh, Majid Univ Tehran Coll Sci Sch Math Stat & Comp Sci Tehran Iran Kharazmi Univ Fac Math Sci & Comp Tehran Iran

In this paper, the behavior of the solutions of a multi-objective optimization problem, whose the objective functions are perturbed by adding a small linear term, is analyzed. In this regard, a new notion of Lipschitzian stability, by means of the Aubin property of the solution set, is defined. Lipschitz stable locally efficient solutions, as generalization of tilt/full stable solutions, are introduced and characterized by modern variational analysis tools. Applying the weighted sum method, the relationships between these solutions and full-stable local optimal solutions of the scalarized problem are investigated. The key tools in deriving our results come from the first- and second-order variational analysis.

关键词： Variational analysis Perturbation in optimization multi-objective programming Aubin stability Tilt-stability Full-stability

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A dietary management recommendation model based on analytic hierarchy process and multi-objective programming for regular out-diners in Taiwan

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SERVICE ORIENTED COMPUTING AND APPLICATIONS 2024年第2期18卷 153-162页

作者： Li, Jung-Bin Fu Jen Catholic Univ Dept Stat & Informat Sci New Taipei Taiwan

This academic paper delves into the intricacies of dining out and dietary management, aiming to provide an effective solution to the multifaceted challenges faced by regular out-diners in Taiwan. The research centers on the development and application of an innovative hybrid model that combines the analytic hierarchy process (AHP) and multi-objective programming (MOP) to facilitate dietary planning, thereby accommodating individual preferences, expert insights, and the recommended daily intake levels for six categories of essential nutrients. The model is designed to enable a dynamic adjustment of preference coefficients when decision-makers provide their preferences, resulting in personalized dietary recommendations. However, it is noted that solutions adhering to predefined budget constraints may sometimes fall short of identifying entirely satisfactory dietary combinations. Furthermore, a significant challenge identified in this study pertains to the availability of food products at chain restaurants and stores. These products often exhibit deficiencies in essential nutrients while offering an excess of dietary energy. The research reveals that when individuals adhere to recommended dietary combinations, they can attain nutrient intake levels that closely approximate suggested values. In this study, the AHP-MOP model demonstrates enhanced stability and superior adherence to the principles of healthy dietary planning, ultimately yielding dietary combinations associated with a higher perceived value within the same budgetary constraints than the MOP-only model. With the regional limitation of model, the study underscores the potential for enhancing the model's practicality by expanding the product database, thereby contributing to the improved dietary well-being of regular out-diners.

关键词： multi-objective programming Analytic hierarchy process Dietary control Dietary reference intake

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Improved semi-infinite interval type-2 fuzzy multi-objective programming with integrated multi-criteria decision analysis for sustainable water resource management

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JOURNAL OF WATER PROCESS ENGINEERING 2025年 73卷

作者： Zhang, Xi Jin, Lei Fan, Yurui Wang, Li Liu, Jing Gao, Pangpang Xiamen Univ Technol Coll Environm Sci & Engn Xiamen 361024 Fujian Peoples R China Brunel Univ London Dept Civil & Environm Engn Uxbridge UB8 3PH Middx England Xiamen Univ Technol Coll Math & Stat Xiamen 361024 Fujian Peoples R China

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.

关键词： Interval type-2 fuzzy Semi-infinite programming multi-objective programming MCDA Risk control Water resources management

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Study on Location-selection of Shared Bicycle Parking Sites Based on multi-objective programming 7

Study on Location-selection of Shared Bicycle Parking Sites ...

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7th International Conference on Traffic Engineering and Transportation System (ICTETS)

作者： Chen, Yuan Hu, Hang Wuhan Text Univ Sch Math & Phys Sci Wuhan 430073 Peoples R China

ISBN: (纸本)9781510674479

With the rapid development of shared bicycles in recent years, it not only facilitates urban residents, but also brings several problems to urban traffic, mainly in disorderly parking. In order to solve the disorderly parking of shared bicycles, this paper takes the Yangguang Campus of Wuhan Textile University for example and considers the trip demand of teachers and students. We choose the cosine distribution time satisfactory function as the service quality level function to quantify the quality of service, which can reflect the distance between demanding points and parking sites to users' satisfaction. Then we establish a multi- objective integer planning location-selection model based on gradual coverage method, which aims at maximizing service quality and minimizing the number of parking sites. We use LINGO to calculate the model with actual survey data. The results show that the solution of the location-selection model is close to the reality and of certain practical significance.

关键词： location selection shared bicycle gradual coverage multi-objective programming

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Optimizing system reliability through selective maintenance allocation: A novel multi-objective programming approach using neutrosophic fuzzy concept

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QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2023年第7期39卷 2784-2806页

作者： Kamal, Murshid Gupta, Srikant Jalil, Syed Aqib Ahmed, Aquil Aligarh Muslim Univ Dept Stat & Operat Res Aligarh India Jaipuria Inst Management Dept Operat & Decis Sci Jaipur India Sohar Univ Fac Business Sohar Oman Sohar Univ Fac Business Sohar 311 Oman

Selective maintenance refers to the problem of decision-making on how to maintain a multi-component complex system that can be repaired or replaced. The goal is generally to plan ahead in order to improve the likelihood of success for future maintenance tasks. In this article, we proposed a multi-objective decision-making model for maximizing the system reliability of a multi-component systems. The objective functions represent the reliability of the sub-systems arranged in series comprising of components arranged in parallel forms. The cost and total time incurred in the repair/replacement activities are considered as two sets of constraints in the proposed model. Fuzzy logic is incorporated to deal with the inherent uncertainty that exists in the parameters involved in the proposed model. To solve the uncertain multi-objective selective maintenance model, we have proposed four-valued neutrosophic technique. The proposed solution methodology combines the concept of four-valued neutrosophic fuzzy set with fuzzy goal programming technique. Four linear membership functions for the degrees of truth, uncertainty, contradiction, and false are used to obtain the compromise solution through the proposed technique. To determine the feasibility and applicability of the proposed model and solution methodology, a case problem of multi-component system of an aircraft gas turbine engine is studied.

关键词： fuzzy goal programming multi-objective programming neutrosophic fuzzy sets selective maintenance problem system reliability

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Machine learning techniques and multi-objective programming to select the best suppliers and determine the orders

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MACHINE LEARNING WITH APPLICATIONS 2025年 19卷

作者： ul Husna, Asma Amin, Saman Hassanzadeh Ghasempoor, Ahmad Toronto Metropolitan Univ Dept Mech Ind & Mechatron Engn Toronto ON Canada

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.

关键词： Supplier selection Order allocation Machine learning multi-objective programming Purchasing Optimization

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