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11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Gao, Yingao Ding, Xiangqian Li, Song Guo, Baoqi College of Computer Science and Technology Ocean University of China Qingdao China Qingdao Haida Nova Software Consulting Co. Qingdao China

ISBN: (纸本)9798350333664

In today's dynamic and rapidly evolving business landscape, collaborative supply chain management has become a research hotspot in enterprise management. This paper aims to develop a comprehensive supply chain collaboration system by integrating the combination weighting method and multi-objective programming. The critical focus areas encompass fabric supplier selection, order allocation, and product delivery. An evaluation system tailored to the enterprise's characteristics is established for fabric suppliers to achieve this. The comprehensive weighting method is utilized to assign weights to evaluation indicators. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is subsequently used to rank the suppliers. Additionally, considering the unique attributes of the clothing and textile industries, a model is developed for order allocation and product delivery. This model aims to minimize the overall expenses of the supply chain, maximize the weighted value of fabrics considering suppliers' priorities, and meet the order demand from distributors. The applicability and effectiveness of the proposed supply chain collaboration system are validated through actual case studies and the utilization of the Gurobi solver. © 2023 IEEE.

关键词： multi-objective programming supply chain collaboration system TOPSIS

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Optimal Allocation of Water Resources of Beijing-Tianjin-Hebei based on multi-objective programming

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2nd International Conference on Energy and Environmental Protection (ICEEP 2013)

作者： Zhang, Chaoliang Fang, Yong Luo, JinChuan Bo, Lin Chinese Acad Sci Acad Math & Syst Sci Beijing Peoples R China

ISBN: (纸本)9783037857427

Water resources are the most valuable natural resources for human's survival and development, and the strategic resources of the national economic and social development. Reasonable utilization and allocation of water resources are the fundamental guarantee for the sustainable development strategy in China. So this paper first forecasts the demand of water for each region, then establishes a multi-objective optimization model of water resources and investigates quantitative methods for the social, economic and environment objectives. According to the specific circumstances of each region, we optimally allocate the water resources in Beijing-Tianjin-Hebei.

关键词： Water Resources Optimal allocation multi-objective programming

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Adapting to climate change in arid agricultural systems: An optimization model for water-energy-food nexus sustainability

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AGRICULTURAL WATER MANAGEMENT 2024年 303卷

作者： Radmehr, Riza Brorsen, B. Wade Shayanmehr, Samira Oklahoma State Univ Dept Agr Econ Stillwater OK 74078 USA Ferdowsi Univ Mashhad Dept Agr Econ Mashhad *** Iran

Sustainable management of water, energy, and food (WEF) under climate change will be a significant challenge for arid agricultural systems. This study developed a fractional non-linear multi-objective programming (FNLMOP) model to optimize resource allocation and improve agricultural sustainability in these systems under climate change. The model was designed in the framework of the WEF nexus to simultaneously improved energy productivity (profit/energy), and water productivity (profit/water), while mitigating environmental damage (damage to groundwater resources/output) and ensuring food security in an arid watershed in Iran. The long Ashton research station weather generator (LARS-WG) and the coupled model intercomparison project 6 (CMIP6) were employed to project climate parameters for both future dry and wet conditions. The sustainability of the optimal solutions was then assessed using a hybrid criteria importance through intercriteria correlation (CRITIC)-VIKOR approach. The optimal solutions revealed a reduction in the land under cultivation and produced less water-intensive crops. The optimization model can ensure WEF security, enhancing agricultural system sustainability by optimizing crop cultivation patterns and resource allocation. Current crop choices were highly inefficient with the bigger changes being from the current crops to optimal crops. Climate change showed a substantial but lesser influence on optimal crop choice.

关键词： Crop pattern multi-objective programming Optimal resource allocation Sustainable development

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Water-agriculture-ecology nexus synergetic management based on spatiotemporal equilibrium and water transformation: A case study in Aksu River Basin, China

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AGRICULTURAL WATER MANAGEMENT 2024年 303卷

作者： Wang, Taishan Su, Xiaoling Wu, Haijiang Northwest A&F Univ Key Lab Agr Soil & Water Engn Arid & Semiarid Area Minist Educ Yangling 712100 Peoples R China Northwest A&F Univ Coll Water Resources & Architectural Engn Yangling 712100 Shaanxi Peoples R China

The temporal variability and spatial heterogeneity characteristics of the water-agriculture-ecology (WAE) nexus system have aggravated the difficulties in its synergetic management. Besides, in the inland river basin, the surface water and groundwater are tightly linked by the combination of canal and well irrigation. To address these issues, a spatiotemporal equilibrium-water transformation based water-agriculture-ecology nexus synergetic management (SEWT-WAE) model was proposed by incorporating a spatio-temporal robust optimization method and linear water transformation model. The SEWT-WAE model was then applied to the Aksu River Basin, an inland river basin of Xinjiang, China. The results indicated that the SEWT-WAE model was highly effective in achieving spatiotemporal equilibrium in groundwater balance and ecological water utilization, as well as in the integrated management of surface water and groundwater across upstream and downstream regions. The optimal synergetic management scheme was obtained based on the coordinated development degree. Compared to the current situation: (i) the irrigation amount provided by the surface water (groundwater) in the Tabei (Tanan) irrigation district was increased (decreased) by 21.4 % (70.2 %);(ii) the irrigated areas of grain crops and gardens were increased by 30.4 % and 20.1 %, respectively, while the irrigated area of cotton was decreased by 19.4 %;(iii) the ecological water utilization of the Populus euphratica forest was increased by 17.81 %. Overall, this study presents a new optimization model for achieving spatiotemporal equilibrium and conjunctive use of surface water and groundwater and provides decision support for WAE nexus synergetic management in the inland river basin.

关键词： multi-objective programming Robust optimization Conjunctive use multiple criteria analysis Water resource management Irrigation water

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Particle Swarm Optimization-Based multi-objective Planning Model for Marketing Strategy Decision

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2024年第16期33卷

作者： Li, Bohan Guo, Qi Univ Illinois Dept Biostat Chicago IL 60607 USA Univ Illinois Dept Business Adm Champaign IL 61820 USA

Intelligent algorithms have shown promise in supporting marketing strategy decisions through data mining. However, existing methods have primarily relied on expertise, lacking autonomous decision-making abilities. Consequently, a marketing strategy decision model based on particle swarm optimization and multi-objective programming is proposed. This study first explores the potential for integrating particle optimization and multi-objective programming models partially, and then assesses the overall effectiveness of each marketing strategy by defining a fitness function. Subsequently, the particle swarm optimization algorithm is employed to search for and optimize decision variables to identify the optimal combination of marketing strategies. Finally, several simulation experiments are conducted using external real data. The research findings indicate that the algorithm's error rate in this study was initially 0.23. However, after 500 training sessions, it decreased to 0.08 and maintained a relatively low level. The proportion of marketing strategy revenue increased by 15.2 percentage points between 0 and 100 training sessions, then remained relatively stable at over 30%. Its revenue proportion continued to rise during the training process, significantly surpassing that of other algorithms.

关键词： Particle swarm optimization multi-objective programming decision-making algorithm optimization

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Sustainable operations-oriented painting process optimisation in automobile maintenance service

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JOURNAL OF CLEANER PRODUCTION 2021年 324卷 129191-129191页

作者： Yang, Qin Meng, Xin Zhao, Huan Cao, Cejun Liu, Yang Huisingh, Donald Sichuan Normal Univ Sch Business Chengdu 610101 Peoples R China Chongqing Technol & Business Univ Sch Management Sci & Engn Chongqing 400067 Peoples R China Linkoping Univ Dept Management & Engn SE-58183 Linkoping Sweden Univ Vaasa Dept Prod Vaasa 65200 Finland Univ Tennessee Inst Secure & Sustainable Environm Knoxville TN USA

Building a more sustainable society is an urgent requirement for today's service-oriented manufacturing enterprises, such as automobile maintenance firms. In automobile maintenance service, traditional painting process scheduling scheme usually only considers the profits of enterprises, ignoring the requirements of customers or other stakeholders. To address this gap and achieve sustainable operations of enterprises in the long term, this paper concentrated on the vehicle scheduling of painting process problem with the concern of the demands of managers, workers, customers, governments and non-government environmental protection organisations. This problem was formulated as a nonlinear 0-1 integer programming model to minimise makespan (MP), total pollutant emissions (TPE) and total customers' perceived dissatisfaction (TCPDS). A genetic algorithm was designed to solve the model, and a practical case using data from both the information system and the survey was performed to test the performance of the proposed model and algorithm. Computational results revealed that the genetic algorithm performed well in terms of validity and stability. Pareto solutions demonstrated that optimising task sequences helped increase customers' perceived satisfaction while improving the makespan of vehicle painting, decreased paint waste, and reduced worker health and safety risks. Some of the increases in the percentage of well-timed customer service reservations were catalysed by the method that combined tiered pricing, related to delivery times, the automobile painting efficiency, which improved customers' perceived satisfaction. This paper also further guides managers to incorporate sustainable development into operations in service-oriented manufacturing enterprises.

关键词： Painting scheduling Service-oriented manufacturing Sustainable operations multi-objective programming Pareto solutions

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A fuzzy compromise approach for solving multi-objective stratified sampling design

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NEURAL COMPUTING & APPLICATIONS 2021年第17期33卷 10829-10840页

作者： Ghufran, Shazia Gupta, Srikant Ahmed, Aquil Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India Jaipuria Inst Management Jaipur Rajasthan India

In this paper, we established a framework for finding out the optimal allocation in the multivariate stratified sample using the fuzzy compromise method. The problem of multivariate stratified sample is formulated as an all integer nonlinear programming problem, and a solution is obtained by using the criterion of "Minimizing the sum of the squares of coefficient of variation for different characteristics." There is also a quantitative illustration being carried out to explain the statistical nature of the approaches and solved through the LINGO program. We have also studied different techniques for comparison.

关键词： Fuzzy compromise allocation multivariate stratified sampling multi-objective programming

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Spatio-temporal evolution analysis of land use change and landscape ecological risks in rapidly urbanizing areas based on multi-Situation simulation - a case study of Chengdu Plain

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ECOLOGICAL INDICATORS 2024年 166卷

作者： Wei, Yali Zhou, Peiyun Zhang, Luoqi Zhang, Yan Sichuan Agr Univ Sch Resources Chengdu 611130 Peoples R China

Land use change in emerging nations raises landscape ecological risks (LERS), hastens the deterioration of urban and rural ecosystem services, endangers human well-being, and undermines sustainable development in the face of rapidly increasing urbanization. Here, using the Chengdu Plain as the study area and long time series data from 2000 to 2020, the optimal time span is selected for multi-context spatio-temporal simulation. The land use map of Chengdu Plain in 2025 under the four scenarios of "Natural Development" (ND), "Economic Priority Development" (END), "Ecological Priority Development" (ELD), and "Sustainable Development" (SD) was simulated, and the multi-indicator landscape ecological risk index (ERI) was generated to compare and analyze the differences between land use and landscape ecological risk under different policy preferences. Subsequently, the land use data from 2025 to 2040 were simulated, the landscape ecological risk pattern was mapped, and the spatial and temporal evolution analysis from 2010 to 2040 was conducted to explore the spatial evolution law of land use change and landscape ecological risk. Based on the results, the high ecological risk aggregation areas are prone to appear in END scenarios, whereas medium-ecological risk aggregation areas are more likely to appear in ELD scenarios, and the government should focus its policy on arable land protection. Moreover, the land use pattern of cultivated land surrounding construction land and forested land surrounding cultivated land, caused by the irrational single-core development pattern and the policy of returning farmland to forests, has exacerbated the landscape ecological risk of the Chengdu Plain, constituting a unique landscape ecological risk pattern. It's also important to remember that the Chengdu Plain's less economically developed regions need to focus on the high-quality development of ecological land use. We adopted high-precision simulation methods to simulate the complex land

关键词： Landscape ecological risk multi-contextual simulation Time-space evolution multi-objective programming PLUS model

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Self-adaptive metaheuristic-based emissions reduction in a collaborative vehicle routing problem

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SUSTAINABLE CITIES AND SOCIETY 2024年 110卷

作者： Kahalimoghadam, Masoud Thompson, Russell G. Rajabifard, Abbas Univ Melbourne Fac Engn & IT Dept Infrastruct Engn Parkville Australia

Global climate change-related initiatives such as the 2015 Paris Agreement have highlighted the necessity of sustainable transportation. Nevertheless, the rapid growth of e-commerce has notably escalated vehicle kilometres travelled (VKT) and CO2 emissions within cities, posing a direct challenge to sustainability initiatives. To address these challenges, this study formulates a collaborative multi-depot green vehicle routing problem. This model utilises micro-consolidation centres (MCCs) as shared hubs alongside a microscopic approach linking emission rates to vehicle and route characteristics, in order to assess MCCs' effectiveness in reducing CO2 emissions. Introduced here is an innovative self-adaptive metaheuristic algorithm hybridising intelligent water drops and simulated annealing. This methodology differs from established approaches by incorporating a feedback control system that actively monitors the algorithm's performance and convergence towards the global minimum solution. Through continuous adjustments to algorithm parameters via a feedback loop, this methodology strikes a balance between exploitation and exploration. The algorithm is tested in a context-specific approach, first applying it to the Cordeau benchmark and comparing it with previous state-of-the-arts, followed by a case study comparing the collaborative network to an independent one. This approach achieves 43 % and 25 % reductions in VKT and emissions, respectively, enhancing urban logistics networks' efficiency and sustainability.

关键词： MDVRP multi-objective programming Network distribution design Hybrid metaheuristics algorithm Comprehensive Modal Emission Model Knowledge-based systems

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Efficient and equitable irrigation management: A fuzzy multi-objective optimization model integrating water movement processes

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 371卷 123164页

作者： Chang, Hong Li, Gang Zhang, Chenglong Huo, Zailin China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China China Agr Univ State Key Lab Efficient Utilizat Agr Water Resourc Beijing 100083 Peoples R China

This study presents a robust multi-objective model for optimizing irrigation water allocation to balance economic benefits, water equity and irrigation efficiency in irrigation decisions under uncertainty. Daily water movement among irrigation, soil, groundwater, and drainage is modeled through water balance simulation and integrated into an optimization model considering economic, social, and resource objectives. To effectively manage conflicts arising from multiple objectives under uncertainty, interval multi-objective programming and fuzzyboundary interval programming are employed. Here, interactive algorithms are used to align constraint feasibility with objective satisfaction to generate optimal solutions for irrigation water allocation. The model's applicability is demonstrated within the Hetao Irrigation District, addressing the rising conflicts between irrigation water supply and demand. The optimization model aims to maximize net economic benefits, minimize Gini coefficient and the proportion of blue water utilization in irrigation water, incorporating daily soil water and groundwater movement processes. By setting five feasibility levels, optimal water allocation solutions are derived for five irrigation subareas and three crops across their entire growth periods. The results analysis shows that an increased feasibility level makes the uncertainty range of the objective values decrease while lower feasibility levels lead to higher satisfaction with the objective values. Moreover, it is found that the decision satisfaction peaks at a feasibility level of 0.9 after balancing feasibility and objective satisfaction, aligning more closely with the decision maker's expectations. At this level, the economic benefit is [3.62, 13.60] x 109 Yuan. Compared to a feasibility level of 1.0, the average range of the economic benefits increases by 122.50 x 106 Yuan, and the Gini coefficient decreases from [0.7973, 0.7997] to [0.7963, 0.7996]. Therefore, the above results c

关键词： multi-objective programming Irrigation planning Physical processes Interactive fuzzy programming Uncertainty Decision-making

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