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A goal programming approach to lean production system implementation

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2023年第1期74卷 403-416页

作者： Karakutuk, S. Serhat Ornek, M. Arslan Yasar Univ Grad Sch Izmir Turkey Yasar Univ Dept Ind Engn Izmir Turkey

Companies use different production policies to ensure customer demands are satisfied in time. To track the performance of production policies some important Key Performance Indicators related to production control and management are On-Time Delivery (OTD), machine or line productivity (OEE - Overall Equipment Efficiency), optimization of inventory levels between workstations (WIP), customer satisfaction i.e. prioritization of customer orders according to requirements of the customer, and backlog minimization. In this study, a real-life production management problem is described, modelled, and solved to improve customer delivery rate and, to plan manufacturing orders using lean production tools. Currently, the Make-to-Stock policy is used for semi-finished materials. The problems encountered are low customer service level, high level of WIP between operations and efficiency losses. Therefore, the goal of this study is to increase efficiency (OTD, OEE, and customer satisfaction) by minimizing setup time, decreasing WIP by minimizing earliness, backlog quantity level and improving service level by minimizing lateness of orders. Since these goals contradict each other, we propose a multi-objective mathematical formulation with a setup carryover strategy. Then we formulate a Goal programming (GP) model and solve it by using different GP variants and the normalization method. Finally, we discuss numerical results and provide our final remarks and conclusions.

关键词： Goal programming multi-objective linear programming push pull scheduling lean production planning

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Artificial intelligence-enabled smart city management using multi-objective optimization strategies

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EXPERT SYSTEMS 2025年第1期42卷

作者： Pinki Kumar, Rakesh Vimal, S. Alghamdi, Norah Saleh Dhiman, Gaurav Pasupathi, Subbulakshmi Sood, Aarna Viriyasitavat, Wattana Sapsomboon, Assadaporn Kaur, Amandeep Lovely Profess Univ Dept Math Phagwara Punjab India Ramco Inst Technol Dept Artificial Intelligence & Data Sci Rajapalayam India Princess Nourah Bint Abdulrahman Univ Coll Comp & Informat Sci Dept Comp Sci Riyadh Saudi Arabia Lebanese Amer Univ Dept Elect & Comp Engn Byblos Lebanon Chitkara Univ Ctr Res Impact & Outcome Rajpura Punjab India Graph Era Deemed Univ Dept Comp Sci & Engn Dehra Dun India Lovely Profess Univ Div Res & Dev Phagwara India Middle East Univ MEU Res Unit Amman Jordan VIT Chennai Sch Comp Sci & Engn Chennai India Sanskriti Sch New Delhi India Chulalongkorn Univ Fac Commerce & Accountancy Chulalongkorn Business Sch Bangkok Thailand Chitkara Univ Chitkara Ctr Res & Dev Baddi Himachal Prades India Chandigarh Univ Dept Comp Sci & Engn Univ Ctr Res & Dev Mohali India

This article outlines an integrated strategy that combines fuzzy multi-objective programming and a multi-criteria decision-making framework to achieve a number of transportation system management-related objectives. To rank fleet cars using various criteria enhancement, the Fuzzy technique for order of preference by resemblance to optimum solution are initially integrated. We then offer a novel multi-objective Possibilistic linear programming (MOPLP) model, based on the rankings of the vehicles, to determine the number of vehicles chosen for the work while taking into consideration the constraints placed on them. The search for optimal solutions to MOPs has benefited from the decades-long development of classical optimisation techniques. As a result of its potential for use in the real world, multi-objective optimisation (MOO) under uncertainty has gained traction in recent years. Recently, fuzzy set theory has been used to solve challenges in multi-objective linear programming. In this paper, we present a method for solving MOPs that makes use of both linear and non-linear membership functions to maximize user happiness. A hypothetical case study of transportation issue is taken here. This innovative approach improves management for the betterment of transportation networks in smart cities. The method is a more robust and versatile approach to the complex difficulties of contemporary urban transportation because it incorporates the TOPSIS method for vehicle ranking and then using Distance Operator and variable Membership Functions in fuzzy goal programming operation on the selected vehicles. The results provide valuable insights into the strengths and limitations of each technique, facilitating informed decision-making in real-world optimization scenarios.

关键词： fuzzy set theory intelligent transportation system multi-objective linear programming smart city TOPSIS

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Supplier selection and order allocation problem using a two-phase fuzzy multi-objective linear programming

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APPLIED MATHEMATICAL MODELLING 2013年第22期37卷 9308-9323页

作者： Nazari-Shirkouhi, Salman Shakouri, Hamed Javadi, Babak Keramati, Abbas Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

The aim of this paper is to solve a supplier selection problem under multi-price level and multi-product using interactive two-phase fuzzy multi-objective linear programming (FMOLP) model. The proposed model attempts to simultaneously minimize total purchasing and ordering costs, a number of defective units, and late delivered units ordered from suppliers. The piecewise linear membership functions are applied to represent the decision maker's fuzzy goals for the supplier selection and order allocation problem, and can be resulted in more flexibility via an interactive decision-making process. To demonstrate effectiveness of the proposed model, results of applying the proposed model are shown by a numerical example. The analytical results show that the proposed approach is effective in uncertain environments and provide a reliable decision tool for integrated multi-objective supplier selection problems. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Supplier selection multi-objective linear programming Fuzzy sets multi-price level multi-product

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Data-driven allocation of renewables quota among regional power industries under the policy of renewable electricity standard

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EXPERT SYSTEMS 2025年第1期42卷

作者： Liu, Xiaohong Xu, Chengzhen Pan, Yinghao Li, Xingchen Zhu, Qingyuan Hefei Univ Technol Sch Humanity & Law Hefei Anhui Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Res Ctr Soft Energy Sci Nanjing Jiangsu Peoples R China Univ Sci & Technol China Sch Management Hefei Anhui Peoples R China Nanjing Audit Univ Sch Accounting Nanjing 211815 Jiangsu Peoples R China

China is struggling to facilitate the application of renewable portfolio standards to realize sustainable economic growth. As such, improving the current distribution mechanism is crucial. In this paper, the context-dependent data envelopment analysis and multi-objective linear programming are combined to allocate the renewables quota for each province. This integrated approach can maximize total electricity generation while minimizing the total CO2 emission with considering the disparity of production technology level. Then, the extended Gini coefficient is employed to assess the fairness of new quota mechanism. We find that (1) the eastern region is the most efficient during the power generation process. During 2016-2019, the efficiency in the western region presents an upward trend. (2) The allocation results indicate that Inner Mongolia and Qinghai have the greatest pressure to absorb renewable energy electricity, while Guangdong and Guizhou can instead reduce the most. Shandong and Inner Mongolia face the greatest burden in conserving non-renewable electricity. (3) Compared to 2020, the newly allocated scheme can mitigate inequality, with the Gini coefficient changing from 0.264 in 2020 to 0.248 after the allocation. Meanwhile, the reallocation reduces the Gini coefficient related to renewable electricity, non-renewable electricity, and CO2 emissions by 0.003, 0.028, and 0.073, respectively at the 2020 level.

关键词： context-dependent DEA Gini coefficient multi-objective linear programming power generation efficiency renewable electricity quota renewable electricity standard

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Optimal selection and investment-allocation decisions for sustainable supplier development practices

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ANNALS OF OPERATIONS RESEARCH 2024年第1期335卷 1-31页

作者： Bai, Chunguang Govindan, Kannan Dhavale, Dileep Univ Elect Sci & Technol China Sch Management & Econ Chengdu Peoples R China Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai Peoples R China Univ Southern Denmark Danish Inst Adv Study Ctr Sustainable Supply Chain Engn Dept Technol & Innovat DK-5230 Odense M Denmark Yonsei Univ Yonsei Frontier Lab Seoul South Korea Woxsen Univ Sch Business Sadasivpet Telangana India Clark Univ Grad Sch Management 950 Main St Worcester MA 01610 USA

Organization's sustainability performance is influenced by its suppliers' sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented.

关键词： Sustainable supplier development Investment allocation Environmental DEMATEL NK model multi-objective linear programming

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Urban land use optimization prediction considering carbon neutral development goals: a case study of Taihu Bay Core area in China

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CARBON BALANCE AND MANAGEMENT 2024年第1期19卷 39页

作者： Tang, Mingfang Rong, Yuejing Zheng, Lifu Luo, Yue Li, Kai Fan, Xin Chinese Acad Sci Res Ctr Ecoenvironm Sci State Key Lab Urban & Reg Ecol Beijing 100085 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing 100085 Peoples R China Sichuan Agr Univ Dept Landscape Architecture Chengdu 611130 Sichuan Peoples R China Gannan Normal Univ Sch Geog & Environm Engn Ganzhou 341000 Peoples R China China Univ Geosci Ctr Turkmenistan Studies Wuhan 430074 Peoples R China

BackgroundGiven the increasing commitment of numerous nations to achieving future carbon neutrality, urban development planning that integrating carbon storage considerations plays a crucial role in enhancing urban carbon efficiency and promoting regional sustainable development. Previous studies have indicated that optimizing land use structure and quality is essential for regional carbon storage management. Taking the core area of Taihu Bay as study area, this study innovatively combined high-precision urban 3D data to account for the whole urban carbon pools of buildings, vegetation, soils, water. Then, multi-objective linear programming model and PLUS (Patch-generating Land Use Simulation) model were applied at patch scale to assess and compare carbon storage in various scenarios, considering both carbon storage maximization and urban development *** results were presented as follows. (1) Urban woodland carbon pool accounts for only a fraction of total carbon pool, and the role of soil and building carbon pools cannot be ignored. (2) Compared with the current situation, the carbon-growth optimized scenario will lead to the increase of total carbon storage by 38,568.31 tons. (3) Carbon-growth optimized scenario has reduced carbon storage in Woodland, Cropland, Village, Water compared to the Natural growth scenario, but has increased carbon storage in Garden plots, Street, Urban district, Town and other ***, we find that for fast-growing cities, rationally planning built-up areas and woodland areas can achieve the twin goals of economic development and maximizing regional carbon storage. Furthermore, the implementation of new energy policies and projects such as green roofs can help to achieve regional carbon neutrality. The study provides new insights into the accounting of carbon pools within cities and the simulation of fine-grained land use planning based on the dual objectives of carbon stock maximization and urban d

关键词： Carbon neutrality Urban land use optimization PLUS model multi-objective linear programming Carbon storage assessment

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multi-objective cropping pattern optimization and comparative assessment with the food-energy-water nexus

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Water Supply 2024年第12期24卷 4077-4093页

作者： Hacısüleyman, Volkan Özger, Mehmet Graduate School Istanbul Technical University Maslak Istanbul34469 Turkey Department of Construction Technology Vocational School Bilecik Seyh Edebali University Bilecik11230 Turkey Hydraulics Division Civil Engineering Department Istanbul Technical University Maslak Istanbul34469 Turkey

Agriculture is the largest consumer of water, accounting for nearly 70% of global freshwater consumption, and it also uses about 30% of the world’s energy. This creates an increasing challenge for the efficient use of water and energy resources while adequately meeting food demand. Therefore, understanding the interrelations between food, energy, and water resources is crucial. In this study, a multi-objective linear programming model was employed to identify alternative scenarios for optimal cropping areas that minimize water use in agriculture and maximize agricultural income. Different weight coefficients were assigned to these objective functions to generate various cropping scenarios. Once the optimal cropping patterns for each scenario were determined, parameters such as water use, energy requirements, agricultural revenue, and carbon dioxide emissions were calculated based on the food-energy-water nexus. The results for each alternative crop pattern scenario were then analyzed. The results indicate that prioritizing the objective of minimizing water use leads to an average reduction of 3.35% in water use, 1.18% in energy demand, and 0.26% in carbon dioxide emissions, while agricultural income increases by an average of 1% compared to the base scenario. Conversely, when maximizing agricultural income is prioritized, there is an average increase of 2.05% in agricultural income. © 2024 The Authors.

关键词： agricultural production planning crop pattern food-energy-water nexus multi-objective linear programming optimization

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An approach to optimize the cost of transportation problem based on triangular fuzzy programming problem

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COMPLEX & INTELLIGENT SYSTEMS 2022年第1期8卷 687-699页

作者： Das, Sapan Kumar Minist Finance Dept Revenue New Delhi India

In this article, we address a fully fuzzy triangular linear fractional programming (FFLFP) problem under the condition that all the parameters and decision variables are characterized by triangular fuzzy numbers. Utilizing the computation of triangular fuzzy numbers and Lexicographic order (LO), the FFLFP problem is changed over to a multi-objective function. Consequently, the problem is changed into a multi-objective crisp problem. This paper outfits another idea for diminishing the computational complexity, in any case without losing its viability crisp LFP issues. Lead from real-life problems, a couple of mathematical models are considered to survey the legitimacy, usefulness and applicability of our method. Finally, some mathematical analysis along with one case study is given to show the novel strategies are superior to the current techniques.

关键词： Fully fuzzy linear programming linear fractional programming linear programming multi-objective linear programming Triangular fuzzy number Lexicographic order

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SOLVING THE multi-objective FRACTIONAL SOLID TRANSPORTATION PROBLEM BY USING DIFFERENT OPERATORS

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Journal of Mathematical Sciences (United States) 2025年第1期289卷 141-153页

作者： Kara, Nurdan Tiryaki, Fatma Naval Training and Education Command Kocaeli 41900 Turkey Department of Mathematics Yildiz Technical University Istanbul 34220 Turkey

This research delves into a complex problem known as the multi-objective fractional solid transportation problem (MFSTP), which deals with various fractional ratios such as cost/profit. The problem involves three main components: origin, destination, and product type or mode of transportation. While this research offers a solution to the MFSTP, it also examines the effects of different aggregation operators. In multi-objective problems, finding Pareto optimal solutions that consider the balance between objectives can be achieved through different methods. Utilizing aggregation operators, this study has found a variety of Pareto optimal solutions, expanding the decision-maker’s options. This means that it presents the decision-maker with a set of potential solutions. This allowed them to evaluate and select the operator that best suited the problem by comparing the various solutions obtained. To illustrate the solution methodology, a numerical example is provided and the obtained solutions are compared. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Aggregation operators Fractional programming Fuzzy mathematical programming multi-objective linear programming Solid transportation problem

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WEIGHTED ITERATION ALGORITHM FOR SOLVING BI-objective linear programming PROBLEM

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2024年第3期20卷 755-770页

作者： Wang, Shuoqi Wang, Zhanzhong Jilin Univ Transportat Coll 5988 Renmin Rd Changchun 130025 Peoples R China

Based on the multi-objective linear weighted method and the characteristic that the sum of the weighted coefficients of the bi-objective function is 1, a weighted iteration algorithm for solving bi-objective linear optimization has been proposed. The basic principle of the algorithm is that when the weighted coefficients increase gradually from a very small value to 1, an efficient solution can be obtained. The iteration algorithm needs convergence conditions. This paper proves the relationship between the iterative convergence conditions and the optimal solution of the objective function, and multiple efficient solutions can be obtained by iteration. According to the actual demand of the project, a method of determining the most efficient solution is given. The main advantage of the algorithm is that the implementation process of the weighted iteration algorithm only needs the optimal solution of a single objective function, and there is no complex process or algorithm for solving weighted coefficients. The algorithm is simple and effective, and overcomes the shortcomings of the existing algorithms that have the complex parameter setting and solving process. The examples and application show that the weighted iteration algorithm is scientific and correct, and it is easy to be used and programmed and can play an important role in practical engineering application.

关键词： linear programming Iteration algorithm Bi-objective linear programming multi-objective linear programming Mathematical programming

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