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Hierarchical goal programming approaches to solve a discrete-time formulation for the aircraft recovery problem of a Brazilian oil and gas company

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2025年第3期32卷 1343-1374页

作者： Fantazzini, Tarley Mansur Vieira, Thiago Morabito, Reinaldo Munari, Pedro Univ Fed Sao Carlos Dept Prod Engn BR-13565905 Sao Carlos SP Brazil

We address the aircraft recovery problem faced by a Brazilian oil and gas company during its offshore operations. This problem involves hiring helicopters from an outsourced company to transport personnel from an airport to maritime units. The performed flights are subject to disruptions and might require rescheduling. To assist with decision-making in such situations, we introduce a discrete-time integer linear programming (ILP) model that considers company-specific attributes, including a lexicographic objective function that prioritizes (i) the reduction of flight transfers to the next day;(ii) the reduction of helicopter utilization;and (iii) the reduction of flight delays of the day. We develop four different solution approaches using hierarchical goal programming based on the proposed model, aided by enhancements and valid inequalities. Computational experiments using both real-world and simulated instances demonstrate that our approaches can provide effective solutions for most instances using a general-purpose ILP solver within acceptable computation times.

关键词： aircraft recovery problem helicopter flights integer linear programming goal programming offshore platforms oil and gas companies

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The relevance of goal programming for financial portfolio management: a bibliometric and systematic literature review

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ANNALS OF OPERATIONS RESEARCH 2025年第2期346卷 917-943页

作者： Colapinto, Cinzia Mejri, Issam IPAG Business Sch 4 Bd Carabacel F-06000 Nice France Ca Foscari Univ Venice Dept Management Cannaregio 873 I-30121 Venice Italy EDC Paris Business Sch OCRE Res Lab Paris France

goal programming models have been highly relevant for portfolio management and selection due to their ability to handle multiple conflicting objectives simultaneously. These models possess simple and effective and features that support the decision-making process by incorporating different types of risk. Using a bibliometric approach, we collected 155 articles published from 1973 to 2022 from journals indexed in the Scopus database. Multiple software platforms (RStudio, VOSviewer, and Excel) were employed to analyze the data and depict the most active scientific actors in terms of countries, institutions, sources, and authors. Our review revealed three different stages and an upward trajectory in the publication trend starting from 2003 and found the predominant application of some goal programming models, such as the stochastic, fuzzy, and polynomial models. Moreover, we discovered that Spain, the USA, and China were the top three contributors to the literature, indicating a global interest in this area. The global relevance of goal programming is confirmed by the top 20 authors and their collaboration networks. We observed the dialogue between different disciplines, namely Decision Science and Management/Finance. Our study contributes to the body of knowledge in the intersection between goal programming and financial portfolios by (1) identifying the most influential articles and authors on this topic and (2) mapping and visualizing the trends in this field of research through network and cluster analysis.

关键词： goal programming Financial portfolio Bibliometrix Bibliometric analysis Content analysis Network analysis

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Modified goal programming approach for solving multi-objective environmental management problem

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ANNALS OF OPERATIONS RESEARCH 2025年第2期346卷 1767-1783页

作者： Singh, Sujeet Kumar Yadav, Vinay Indian Stat Inst Hyderabad 500007 India Indian Inst Technol Kharagpur Vinod Gupta Sch Management Kharagpur 721302 India

Although goal programming is one of the most used techniques for modeling and solving multi-objective optimization problems due to modeling elegance and mathematical simplicity. However, the existing goal programming methods have some deficiencies in assigning the weights and then finding the solution per the objectives' priority to tackle the incommensurabilty in heterogeneous objectives. Therefore, this article proposes an efficient scalarization technique to solve the multi-objective optimization problem by introducing a modified goal function. The performance of the proposed method is evaluated using some closeness measure to the ideal solution for several test problems. A real application of the proposed method is illustrated in finding the best locations to establish municipal solid waste (MSW) management intermediate facilities in Nashik city (India). The model selects the three best locations out of the given eight potential locations to establish facilities by considering environmental and economic objectives. Overall, this study provides a theoretical advancement supported by a real-life MSW management application.

关键词： goal programming Multiple objective programming Efficient solutions Municipal solid waste management

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Optimization of the food distribution process using the goal programming technique

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OPSEARCH 2025年 1-23页

作者： Godoi, Leticia Ferreira Aranha, Flavia Queiroga Coral, Mariele Colletti Cantane, Daniela Renata Sao Paulo State Univ UNESP Inst Biosci Postgrad Program Biometr BR-18618689 Botucatu SP Brazil Sao Paulo State Univ UNESP Inst Biosci Dept Human Sci & Nutr & Food Sci BR-18618689 Botucatu SP Brazil Food Bank Lourdes Pedutti Soares Batista BR-18611020 Botucatu SP Brazil Sao Paulo State Univ UNESP Inst Biosci Dept Biodivers & Biostat BR-18618689 Botucatu SP Brazil

Food banks play a crucial role in the combat against hunger and food insecurity, being responsible for distributing donated food to the population who are facing restrictions in their access to food. This process presents several challenges in terms of adopting the principles of equity, efficiency, and effectiveness, including when the amount of food available is insufficient to meet all demands. In this context, this study proposes an optimization model using the goal programming technique applied to food distribution in search of improved agility and equity in the process. The model was implemented and analyzed using a fictional scenario and also applied to a realistic scenario that describes the operation of a Brazilian food bank. The results indicate that Chebyshev goal programming is effective in optimizing the distribution process, and promoting equity and efficiency in the assistance provided to social institutions. This approach is an important tool to help managers develop agile process planning strategies.

关键词： goal programming Optimization Food banks Food distribution

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A Fuzzy goal programming Approach for Production Planning in Packaging Industry 11th

A Fuzzy Goal Programming Approach for Production Planning in...

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11th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2025

作者： Koohathongsumrit, Nitidetch Chankham, Wasana Pongsathornwiwat, Akkaranan Kongkaew, Wanatchapong Department of Statistics Faculty of Science Ramkhamhaeng University Bangkok10240 Thailand Graduate School of Applied Statistics National Institute of Development Administration Bangkok10240 Thailand Department of Industrial and Manufacturing Engineering Faculty of Engineering Prince of Songkla University Songkhla90110 Thailand

ISBN: (纸本)9789819646029

Optimizing production planning problems is often defined by conflicting objectives, such as minimizing costs, maximizing benefits, and meeting product quantity requirements under uncertainties and within fuzzy environments. To overcome these challenges, the fuzzy goal programming (FGP) model was applied. The FGP model can compromise between objectives to achieve optimal membership functions of each objective while simultaneously maximizes the overall achievement function. Moreover, the FGP model was applied to optimize the production planning problem in a realistic case study from the packaging industry. There are eight different objectives and two hard constraints. These objectives involve profitability, costs, and the minimum requirements for each product, allowing for some tolerance. However, cycle time and material usage must strictly adhere to the specified requirements. The results showed that the proposed FGP model effectively optimizes the production planning problem by determining the optimal quantities of each product to be produced and calculating the membership function values for each objective. The model ensures the highest possible overall membership function while strictly satisfying all the production constraints. Moreover, the proposed model was further analyzed under various parameter scenarios reveals that certain objectives probably exceed production capabilities and thus be unachievable in practice. This analysis provides a clearer understanding of feasible operational boundaries. The contributions of this study can be generalized to other industries facing similar multiple goals and uncertain conditions, making it a versatile tool for production optimization. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： goal programming

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Solving an Integrated Project Portfolio Selection and Contractor Selection Problem: Fuzzy goal programming Based on Fuzzy Preference Relations

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FUZZY INFORMATION AND ENGINEERING 2025年第1期17卷 75-107页

作者： Zahedirad, Mostafa Khalili-Damghani, Kaveh Ghezavati, Vahidreza Komijan, Alireza Rashidi Islamic Azad Univ Dept Ind Engn South Tehran Branch Tehran *** Iran Islamic Azad Univ Dept Ind Engn Sci & Res Branch Tehran *** Iran

Several factors affect the flexibility and the complexity of the project selection and the contractor selection problems. Project portfolio managers are expected to select the best combination of projects and contractors considering multiple conflicting objectives in a multi-period planning horizon. In this paper, we propose an integrated project portfolio optimization and contractor selection problem. The problem is modeled through a multi-objective Mixed Integer Linear programming (MILP) model. Three solution approaches including goal programming (GP), Fuzzy goal programming (FGP), and fuzzy goal programming considering a fuzzy preference relationship are proposed. All solution approaches have been applied to a real case. The computational results show the out performance of FGP considering fuzzy relations. The time complexity of the proposed models in the sense of the relation of CPU time and the number constraints and variables of the models were discussed.

关键词： Integer programming Computational modeling programming Planning Mixed integer linear programming Complexity theory Time complexity Portfolios Optimization project selection contractor selection multi-objective mixed integer programming goal programming fuzzy goal programming fuzzy preference relation

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goal programming model for grocery shelf space allocation

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第2期181卷 634-644页

作者： Reyes, Pedro M. Frazier, Gregory V. Baylor Univ Hankamer Sch Business Dept Management & Entrepreneurship Waco TX 76798 USA Univ Texas Dept Informat Syst & Operat Mangement Arlington TX 76019 USA

The highly competitive grocery retail industry has annual sales of roughly half a trillion dollars in the US. While gross margins average about 28% of sales, net profits after taxes are only 1% industry-wide, causing retailers to continually search for operational improvements that increase profitability and improve customer service. One important decision that affects both of these goals is how to allocate shelf space to different products. This paper addresses the specific problem of how to allocate a fixed amount of shelf space to different products within a particular product category, such as pickles or jelly. A nonlinear integer goal programming formulation is proposed that considers both profitability and customer service factors. This decision support tool shows the tradeoffs between increased profitability and improved customer service, and allows the manager to make the best tradeoff for the situation. An alternate approach is also proposed. (c) 2006 Elsevier B.V. All rights reserved.

关键词： goal programming retailing shelf space allocation grocery industry

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goal programming in the context of the assignment problem and a computationally effective solution method

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APPLIED MATHEMATICS AND COMPUTATION 2008年第1期200卷 34-40页

作者： Jahanshahloo, G. R. Afzalinejad, M. Univ Tafresh Fac Math Tafresh *** Iran Teacher Training Univ Fac Math Sci & Comp Engn Tehran *** Iran

This paper develops the goal programming technique to solve the multiple objective assignment problem. The required model is formulated and an appropriate solution method is presented. The proposed method, which is a decomposition method, exploits the total unimodularity feature of the assignment problem and effectively reduces the computational efforts. Some issues related to the efficiency of a GP solution are stated and some specialized techniques for detecting and restoring efficiency are proposed. (C) 2007 Elsevier Inc. All rights reserved.

关键词： goal programming assignment problem multi-objective programming Pareto efficiency Dantzig-Wolfe reformulation

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goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function

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ALEXANDRIA ENGINEERING JOURNAL 2021年第2期60卷 2525-2533页

作者： Uddin, Md. Sharif Miah, Musa Khan, Md. Al-Amin AlArjani, Ali Prince Sattam Bin Abdulaziz Univ Dept Mech & Ind Engn Coll Engn Al Kharj Saudi Arabia Mawlana Bhashani Sci & Technol Univ Dept Math Santosh 1902 Tangail Bangladesh Jahangirnagar Univ Dept Math Dhaka 1342 Bangladesh

In a managerial position, the ultimate objective is to take the right decision for the decision maker (DM) when transportation parameters are uncertain due to the globalization and other uncontrollable influences. In this paper, fuzzy membership function tactic based on goal programming to obtain the desired compromise solution of a multi-objective transportation problem (MOTP) in uncertain environment is proposed where the DM can choose a confidence level for different parameters. On the basis of DM's choice on a particular confidence level, a compromise solution is obtain indicating the satisfaction level of the DM if the problem is feasible for this chosen confidence level. Uncertain normal distribution is used to convert the parameters from uncertain to a certain one. Simple linear programming problem (LPP) is designed using fuzzy linear membership function where the upper and lower values of the objectives are the desired goals of the DM. A numerical illustration is furnished to establish the effectiveness of the designed model whereas the single objective transportation problems are solved by TORA and LPPs are solved by using LINGO for operations research. (C) 2020 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.

关键词： Transportation problem goal programming Uncertain parameter Fuzzy membership function

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goal programming - THE RPMS NETWORK APPROACH

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 1991年第1期42卷 83-93页

作者： SHIM, JP CHUN, SG MISSISSIPPI STATE UNIV DEPT MANAGEMENT & INFORMAT SYSTPO DRAWERMGMISSISSIPPI STATEMS 39762 USA

This paper presents an application of the Resource Planning and Management Systems (RPMS) network approach to the goal programming (GP) problem as an alternative to several other approaches used in the GP process. The... 详细信息

关键词： DECISION SUPPORT SYSTEMS goal programming NETWORK APPROACH

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