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Linear fractional optimization over the efficient set of multi-objective integer quadratic problem

RAIRO-OPERATIONS RESEARCH 2024年第1期58卷 741-758页

作者： Bencheikh, Ali Moulai, Mustapha USTHB Fac Math Dept Operat Res BP32 El Alia 16111 Algeria USTHB Fac Math LaROMaD Lab BP32 El Alia 16111 Algeria

In this paper, we introduce an exact algorithm for optimizing a linear fractional utility function over the efficient set of a multi objective integer quadratic problem. The algorithm is based on the "Branch and Cut" principle, which combines the branching process to ensure decision variables' integrity and efficient cuts built off the non-increasing gradients' directions of objective functions to eliminate inefficient integer solutions. The proposed approach accelerates the convergence to the efficient solution that optimizes the utility function. After presenting and describing the algorithm, a detailed didactic example is illustrated, followed by an experimental study to validate our approach and show computational costs.

关键词： multi-objective programming integer programming quadratic programming fractional programming branch and cut

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Fuzzy Stochastic Genetic Algorithm for Obtaining Optimum Crops Pattern and Water Balance in a Farm

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WATER RESOURCES MANAGEMENT 2016年第12期30卷 4097-4123页

作者： Dutta, S. Sahoo, B. C. Mishra, Rajashree Acharya, S. KIIT Univ Sch Appl Sci Dept Math Bhubaneswar Orissa India Orissa Univ Agr & Technol Coll Agr Engn & Technol Dept Soil & Water Conservat Engn Bhubaneswar Orissa India

This paper is concerned with multi-objective fuzzy stochastic model for determination of optimum cropping patterns with water balance for the next crop season. The objective functions of the model is to study the effect of various cropping patterns on crop production subject to total water supply in a small farm. The decision variables are the cultivated area of different crops at the farm. The water requirement of the crops follows fuzzy uniform distribution and yields in the objective functions are taken as a fuzzy numbers. The model is solved by using fuzzy stochastic simulation based genetic algorithm without deriving the deterministic equivalents.

关键词： Cropping pattern Water balance Genetic algorithm Fuzzy stochastic programming multi-objective programming

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Investigating strategies to reduce CO₂ emissions from the power sector of Taiwan

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2004年第6期26卷 455-460页

作者： Hsu, CC Chen, CY Nan Jeon Coll Technol Dept Management & Informat Tainan 73701 Taiwan Natl Cheng Kung Univ Inst Resources Engn Tainan 70101 Taiwan

This paper investigates strategies to reduce CO2 emissions from the power sector of Taiwan. A multi-objective mix integer model for power generation strategy in Taiwan is proposed. A power supply problem with integer constraints on lowest power generation to meet the practical operation of power unit is also presented. This model can be used to plan future power units' expansion strategy, as well as to study the effect of CO2 emission constraints. Further, this model is used to investigate optimal strategies for stabilizing CO2 emissions to the desired level from the power sector in Taiwan;these accounted for about 40% of CO2 emissions in the country in 2000. Real operational data from the Taiwan Power Company are used for testing the model effectiveness. In addition, recommendations are made for implementation. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： CO2 emissions multi-objective programming power sector

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multi-objective optimization of complex scheduling problems in low-volume low-variety production systems

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2019年 208卷 1-16页

作者： Russell, Arya Taghipour, Sharareh Ryerson Univ 350 Victoria St Toronto ON M5B 2K3 Canada

In this paper, a new approach for solving scheduling problems in low-volume low-variety production systems is proposed. Products assembled in such production systems follow a pre-defined processing order through a series of unique work centers, each budgeted with multiple classifications of resources, responsible to complete a pre-defined statement of work, over the span of an imposed takt-time. Aircraft, heavy aero-structures, and heavy mining and military equipment are examples of products assembled in such production systems. Despite prominent scholarly advancements in sequencing and scheduling optimization of a wide range of production systems, limited research has been reported on mathematical programming approaches for scheduling optimization of activities in low-volume low-variety production systems. This paper fills the gap in the current literature, through the formulation of a set of multi-objective mixed-integer linear mathematical programming models, developed for solving discrete-time work center scheduling problems in low-volume low-variety production systems. Three mathematical models are proposed in this paper, two of which are formulated for scheduling optimization of activities within a work center, differentiated by their objectives and underlying assumptions, reflective of two distinct industrial approaches to scheduling. Additionally, an alternative optimization model is proposed for evaluating a work center's maximum capacity given the complete saturation of resources, recommended for capacity studies and early detection of bottlenecks. The models proposed in this paper are validated and verified for compatibility and reliability through a real-world case study with a global leader in the aerospace industry.

关键词： Low-volume low-variety production systems Large-scale optimization Scheduling optimization multi-objective programming Mixed-integer programming Aerospace assembly line

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Production planning with multiple objectives in decentralized organizations

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 1998年第3期56-7卷 243-252页

作者： Homburg, C Univ Mannheim Chair Operat Res D-68131 Mannheim Germany

The paper presents a procedure for supporting the process of production planning in decentralized organizations. A situation is considered similar to that of the Dantzig/Wolfe algorithm: several divisions use scarce production resources that are controlled by the top management. In contrast to the Dantzig/Wolfe situation, however, all decision makers - on the top- as well as on the base-level - are assumed to have more than one goal. Therefore, within the process of production planning a hierarchical negotiation between top- and base-level takes place, in which interpersonel as well as intrapersonel conflicts have to be solved. The well-known interactive MODM algorithm of Zionts/Wallenius is modified in order to structure the hierarchical negotiation and to model its hierarchical character. The negotiation results in a feasible resource allocation and in a set of aspiration levels for the goals of the top-level which have to be met by the different divisions. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： decentralized organizations coordination production planning multi-objective programming

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Post-pruning in regression tree induction: An integrated approach

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EXPERT SYSTEMS WITH APPLICATIONS 2008年第2期34卷 1481-1490页

作者： Osei-Bryson, Kweku-Muata Virginia Commonwealth Univ Res Inst Dept Informat Syst Richmond VA 23284 USA

The regression tree (RT) induction process has two major phases: the growth phase and the pruning phase. The pruning phase aims to generalize the RT that was generated in the growth phase by generating a subtree that avoids over-fitting to the training data. Most post-pruning methods essentially address post-pruning as if it were a single objective problem (i.e., maximize validation accuracy), and address the issue of simplicity (in terms of the number of leaves) only in the case of a tie. However, it is well known that apart from accuracy there are other performance measures (e.g., stability, simplicity) that are important for evaluating DT quality. In this paper we present an integrated approach to post-pruning phase that simultaneously accommodates multiple performance measures that are important for evaluating RT quality, and obtains the optimal subtree based on user provided preference and value function information. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： regression tree decision tree post-pruning data mining performance measures multi-objective programming mixed integer programming analytic hierarchy process

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Thermo-economic analysis and optimization selection of ORC system configurations for low temperature binary-cycle geothermal plant

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APPLIED THERMAL ENGINEERING 2017年 125卷 153-164页

作者： Liu, Xiaomin Wei, Ming Yang, Luona Wang, Xing Xi An Jiao Tong Univ Sch Energy & Power Engn Dept Fluid Machinery & Engn 28 West Xianning Rd Xian 710049 Shaanxi Peoples R China Chinese Acad Sci Inst Engn Thermophys Energy Storage R&D Ctr Beijing 100190 Peoples R China

multi-objective programming is used to analyze the performance of different organic Rankine cycle (ORC) plant layouts with different working fluids for low temperature binary-cycle geothermal plant. The studied results show that for the considered ORC plant layouts, the optimal overall performance indices increase with the geothermal temperature increasing. For a specific working fluid, the optimal ORC system for overall performance always remains unchanged despite the increase in the geothermal temperature. The optimal schemes of ORC systems vary with the performance indices of ORC system. The optimal scheme for comprehensive performance index is simple cycle with R123 when the geothermal temperature increases from 80 degrees C to 95 degrees C. The optimal scheme for thermal efficiency is regenerative cycle with R123, while the optimal scheme for capital cost is superheated cycle with R123. For the work output and exergy efficiency, the optimal scheme is superheated cycle with R152a when the geothermal temperature varies from 80 degrees C to 85 degrees C, while the scheme of superheated cycle with R134a is better for work output and exergy efficiency when the geothermal temperature is greater than 90 degrees C. This study provides useful references for the researchers selecting the optimal configuration of ORC system for low temperature binary-cycle geothermal plant. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Organic Rankine cycle multi-objective programming Working fluid Geothermal plant

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A multi-stage and multi-supplier inventory model allowing different order quantities

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APPLIED MATHEMATICAL MODELLING 2017年 52卷 613-625页

作者： Chang, Shu-Chin Chang, Ching-Ter Chung Yuan Christian Univ Dept Accounting Taoyuan Taiwan Chang Gung Univ Dept Informat Management Taoyuan Taiwan Chang Gung Mem Hosp Dept Thorac Med Taoyuan Taiwan Ming Chi Univ Technol Dept Ind Engn & Management New Taipei Taiwan

This paper addresses a multi-stage inventory model that allows different order quantities among the selected suppliers to obtain the optimal solutions. To achieve the objective of the study, the single-objective and multi-objective methods are adopted for suitable real world applications. With respect to a single-objective method, this paper aims to minimize the total ordering costs, holding costs, and purchasing costs, subject to the price, quality, and capacity. With respect to a multi-objective method, it focuses on cost minimization, as well as quality and capacity maximization. The proposed model not only considers the allocation of different order quantities among the selected suppliers, but also incorporates the multi-stage inventory problem. Furthermore, a numerical example is provided to illustrate the usefulness of the proposed model and a comparative understanding of various methods. In addition, a simulation test is performed to effectively validate the proposed model which outperforms the previous works. Finally, a sensitivity analysis carried out to investigate the impact of supply chain cost. (C) 2017 Elsevier Inc. All rights reserved.

关键词： multi-objective programming multi-stage inventory model Supply chain system

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A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return

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APPLIED MATHEMATICAL MODELLING 2013年第6期37卷 4165-4176页

作者： Amin, Saman Hassanzadeh Zhang, Guoqing Univ Windsor Dept Ind & Mfg Syst Engn Windsor ON N9B 3P4 Canada

A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper, a CLSC network is investigated which includes multiple plants, collection centres, demand markets, and products. To this aim, a mixed-integer linear programming model is proposed that minimizes the total cost. Besides, two test problems are examined. The model is extended to consider environmental factors by weighed sums and a-constraint methods. In addition, we investigate the impact of demand and return uncertainties on the network configuration by stochastic programming (scenario-based). Computational results show that the model can handle demand and return uncertainties, simultaneously. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Reverse logistics (RL) Closed-loop supply chain (CLSC) Mixed-integer linear programming (MILP) multi-objective programming Stochastic programming

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SDG-oriented multi-scenario sustainable land-use simulation under the background of urban expansion

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第48期29卷 72797-72818页

作者： Zhou, Min Ma, Yuxiang Tu, Jiating Wang, Mengcheng Huazhong Univ Sci & Technol Coll Publ Adm 1037 Luoyu Rd Wuhan Peoples R China

With the continuous improvement of urbanization level and the continuous expansion of city scale, there are some unreasonable land development and utilization problems, which will make the contradiction between people and land more prominent and the risk of ecological environment deterioration more serious. It hinders the sustainable land use (SLU) and then affects the realization of regional Sustainable Development Goals (SDGs). SDGs have become a programmatic document for all countries in the world to implement sustainable development. It provides a guideline and direction for the sustainable urban expansion. The sustainable urban expansion promotes the realization of SDGs worldwide. By combining the SDGs with the urban SLU, this paper obtains the optimized future land-use demand of the multi-scenario city and the urban expansion simulation scenario to the SDGs under the multi-scenario through the uncertain mathematical model (MIFCCP) and the spatial simulation model (PLUS). We find that firstly, the net profit of land use (LNB) reaches the highest value under the economic development scenario (ED), when the probability of environmental constraint violation p = 0.01 and p = 0.15, LNB = [2625.48, 3244.98] x 10(9) CNY, and [2646.95, 3271.51] x 10(9) CNY. Ecosystem service value (ESV) reached the highest value under the sustainable development scenario (SD), when p = 0.01 and p = 0.15, ESV = [75.34, 93.12] x 10(9) CNY, and [72.62, 95.56] x 10(9) CNY. The net carbon emissions from land use (LNC) reached the minimum value in SD scenario, and when p = 0.01 and p = 0.15, the LNC reached [57.46, 71.02] x 10(6) ton and [56.12, 76.04] x 10(6) ton. Secondly, the contribution degree of 15 driving factors to the change of local types is excavated, among which, the driving factors of traffic stations have the highest contribution degree to the change of construction land and cultivated land, and the third-class roads have the highest contribution degree to the change of wetland

关键词： Sustainable land use SDGs multi-objective programming Uncertain model Patch-generating simulation Land use simulation

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