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Compromise mixed allocation using fuzzy programming approach

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2021年第3期91卷 435-444页

作者： Khanam, Nisha Ansari, A. H. Quddoos, Abdul Integral Univ Lucknow Uttar Pradesh India Kejriwal Inst Management & Dev Studies Ranchi Bihar India

In stratified random sampling, Ahsan et al. [Mixed allocation in stratified sampling. Aligarh J Stat. 2005;25:87-97] introduced the concept of 'Mixed allocation' for fixed cost by minimizing the variance of the stratified sample mean which was based on the work of Clark and Steel [Optimum allocation of sample to strata and stages with simple additional constraints. Statistician. 2000;49(2):197-207] for two-stage univariate sampling design. The present manuscript studies the problem of obtaining a 'compromise mixed allocation' in multivariate stratified sampling using fuzzy programming Technique. To exhibit the application of the defined approach, a numerical illustration is considered and solved using Lingo 13.0. In order to demonstrate the superiority of proposed approach, the obtained results have been compared with four other existing approaches.

关键词： Mixed allocation multivariate stratified sampling fuzzy programming approach compromise mixed allocation

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An Effective Hybrid fuzzy programming approach for an Entropy-Based Multi-Objective Assembly Line Balancing Problem

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INFORMATICA 2019年第3期30卷 503-528页

作者： Mahmoodirad, Ali Heydari, Ahmad Niroomand, Sadegh Islamic Azad Univ Dept Math Masjed Soleiman Branch Masjed Soleiman Iran Firouzabad Inst Higher Educ Dept Math Firouzabad Fars Iran Firouzabad Inst Higher Educ Dept Ind Engn Firouzabad Fars Iran

In cases where the balance problem of an assembly line with the aim to distribute the work loads among the stations as equal as possible, the concept of entropy function can be used. In this paper, a typical assembly line balancing problem with different objective functions such as entropy-based objective function plus two more objective functions like equipment purchasing cost and worker time-dependent wage is formulated. The non-linear entropy-based objective function is approximated as a linear function using the bounded variable method of linear programming. A new hybrid fuzzy programming approach is proposed to solve the proposed multi-objective formulation efficiently. The extensive computational experiments on some test problems proves the efficiency of the proposed solution approach comparing to the available approaches of the literature.

关键词： assembly line balancing problem entropy function bounded variable linearization method fuzzy programming approach

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A fuzzy programming approach to Solve Stochastic Multi-objective Quadratic programming Problems

A Fuzzy Programming Approach to Solve Stochastic Multi-objec...

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Computing Conference

作者： Khalifa, Hamiden A. Elgendi, Elshimaa A. Ebraheim, Abdul Hadi N. Cairo Univ Dept OR ISSR Giza Egypt Cairo Univ Dept ORDS FCI Giza Egypt Cairo Univ Dept Math Stat ISSR Giza Egypt

ISBN: (纸本)9783030011741;9783030011734

This article handles the stochastic multi-objective quadratic programming problem (S-MOQP) using a fuzzy programming approach. In S-MOQP problem, both the objective function coefficients matrix and parameters in the constraints both are normally distributed random variables. The S-MOQP problem is converted into the corresponding ordinary multi-objective quadratic programming problem (MOQP). Then, a compromise solution for the MOQP problem is found via a fuzzy programming approach using a linear membership function. The applicability of the proposed algorithm is illustrated by two numerical examples.

关键词： Stochastic multi-objective quadratic programming problem Chance-constrained programming fuzzy programming approach Linear membership function Compromise solution

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Scheduling the sequence of aircraft landings for a single runway using a fuzzy programming approach

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2012年 25卷 15-18页

作者： Tavakkoh-Moghaddam, Reza Yaghoubi-Panah, Mojtaba Radmehr, Farzad Univ Tehran Tehran 111554563 Iran

This paper examines the ways of landing aircraft with the least waiting time in time windows under critical conditions, such as the closest time of landing to the target times for each aircraft or the minimum time of landing the planes. Therefore, we face with two conflict objectives, namely minimizing the total cost of the deviation from the target times and minimizing the completion time of the landing sequence. To solve such a problem, we use a fuzzy programming approach and an estimator for landing the sequence of planes. The results are compared with actual landings. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Runway use Aircraft landing sequencing fuzzy programming approach

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A multi-objective based direct solution approach for linear programming with intuitionistic fuzzy parameters

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JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2018年第2期35卷 1923-1934页

作者： Niroomand, Sadegh Firouzabad Inst Higher Educ Dept Ind Engn Firouzabad Fars Iran

A linear programming with triangular intuitionistic fuzzy parameters is focused in this paper. As a shortcoming, all the solution approaches of the literature for this problem are constructed based on ranking functions, where, use of different ranking functions may result in different solutions. In this study for the first time an approach with no ranking function is developed for the problem. For this aim, the triangular intuitionistic fuzzy objective function is decomposed to a multi-objective function, and the problem is converted to a multi-objective crisp problem. As another contribution, in order to solve the obtained multi-objective problem for its efficient solutions, a new multi-objective optimization approach was developed and suited to the obtained crisp multi-objective problem. The computational experiments of the study, show the superiority of the proposed multi-objective optimization approach over the existing approaches of the literature.

关键词： Linear programming triangular intuitionistic fuzzy number multi-objective optimization fuzzy programming approach

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Formulation and Solution approach for Uncertain Multi-Objective Material Requirement Planning Problem with Multi-Mode Demand, Overtime Production, and Outsourcing Possibilities

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Journal of Systems Science and Systems Engineering 2025年第1期34卷 1-28页

作者： Sadegh Niroomand Dragan Pamucar Ali Mahmoodirad Department of Industrial Engineering Firouzabad Higher Education CenterShiraz University of TechnologyShirazIran Department of Operations Research and Statistics Faculty of Organizational SciencesUniversity of BelgradeBelgradeSerbia Department of Industrial Engineering and Management Yuan Ze UniversityTaoyuan CityTaiwanChina Department of Mechanics and Mathematics Western Caspian UniversityBakuAzerbaijan Department of Mathematics Babol BranchIslamic Azad UniversityBabolIran

Material requirement planning is a type of production planning problems that is used to plan about a final product, its sub-assemblies, and its raw parts simultaneously by considering time phased demands of the final product. In this study a multi-product material requirement planning problem with limited manufacturing resources is considered. As an important novelty, a multi-mode demand strategy is considered in this problem where the total customers’ satisfaction degrees of the selected demand modes is maximized. Furthermore, three types of capacities such as regular, over time, and outsourcing capacities are considered for such system as another novelty. The problem is formulated as a bi-objective model to maximize total profit and total satisfaction degree of the customers simultaneously. To respect the uncertain nature of the problem, it is formulated in a belief-degree based uncertain form. This is for the first time in the literature of material requirement planning that this type of uncertainty is considered. The uncertain problem is converted to a crisp form using some techniques such as expected value model and chance constrained model. Then, a new hybrid form of the fuzzy programming approach is developed to solve the bi-objective crisp formulations. A case study from the petroleum industries of Iran is used to perform the required computational experiments. The required experiments are done, and possible comparisons are made on the obtained results. Furthermore, some managerial insights are given in order to be used in the production system of the case study. According to the obtained results, the proposed hybrid fuzzy programming approach is superior to existing approaches in at least 38 percent of the experiments.

关键词： Material requirement planning multi-mode demand belief-degree based uncertainty multi-objective optimization fuzzy programming approach

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fuzzy Multi-Objective Linear programming Problem Using DM's Perspective

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INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY 2022年第1期14卷 1-17页

作者： Singh, Vishnu Pratap Deshmukh, Madhura Sharma, Kirti Visvesvaraya Natl Inst Technol Dept Math Nagpur Maharashtra India

In this paper, a two-stage method has been proposed for solving fuzzy multi-objective linear programming problem (FMOLPP) with interval type-2 triangular fuzzy numbers (IT2TFNs) as its coefficients. In the first stage of problem solving, the imprecise nature of the problem has been handled. All technological coefficients given by IT2TFNs are first converted to a closed interval and then the objectives are made crisp by reducing a closed interval into a crisp number, and constraints are made crisp by using the concept of acceptability index. The amount by which a specific constraint can be relaxed is decided by the decision maker, and thus, the problem reduces to a crisp multi-objective linear programming problem (MOLPP). In the second stage of problem solving, the multi-objective nature of the problem is handled by using fuzzy mathematical programming approach. In order to explain the methodology, two numerical examples of the proposed methodology in production planning and diet planning problems have also been worked out in this paper.

关键词： Acceptability Index fuzzy programming approach Interval Linear programming Interval Type-2 Triangular fuzzy Numbers Multi-Objective Linear programming Problem

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A hybrid solution approach for fuzzy multiobjective dual supplier and material selection problem of carton box production systems

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EXPERT SYSTEMS 2019年第1期36卷 e12341-e12341页

作者： Niroomand, Sadegh Mahmoodirad, Ali Mosallaeipour, Sam Firouzabad Inst Higher Educ Dept Ind Engn Firuzabad Fars Iran Islamic Azad Univ Dept Math Masjed Soleiman Branch Masjed Soleiman Iran Saxion Univ Appl Sci Hospitality Business Sch Deventer Netherlands

A novel optimization problem of carton box manufacturing industries is introduced in this paper. A mixed integer linear formulation with multiple objective functions is developed in order to determine the value of some criteria of carton raw sheets such as size, amount, and supplier under simultaneous minimization of multiple goals such as purchasing cost of raw sheets under discount policy, wastage remained from raw sheets, and quantity of surplus of carton boxes. In order to cope with the unstable market of this sector, some parameters of the proposed formulation such as demand value of the products and price given for raw sheets are assumed to be fuzzy numbers. To tackle such fuzzy multiobjective problem, first, the fuzzy problem is converted to a crisp form using the concepts of necessity-based chance-constrained modelling approach. Then a new hybrid form of the fuzzy programming approach is proposed to solve the obtained crisp multiobjective problem effectively. Computational experiments on a real case given by a carton box factory show the superior result of the proposed solution approach compared with the well-known multiobjective solution methods taken from the literature.

关键词： fuzzy chance-constrained modelling fuzzy programming approach material selection problem multiobjective optimization supplier selection problem

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Multi-Objective Faculty Course Assignment Problem with Result and Feedback Based Uncertain Preferences

INTERNATIONAL JOURNAL OF MATHEMATICAL ENGINEERING AND MANAGE...

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INTERNATIONAL JOURNAL OF MATHEMATICAL ENGINEERING AND MANAGEMENT SCIENCES 2021年第4期6卷 1055-1075页

作者： Bhoi, Sunil B. Dhodiya, Jayesh M. Sardar Vallabhbhai Natl Inst Technol Dept Appl Math & Humanities Surat Gujarat India

In this paper, a multi-objective faculty course allocation problem with result analysis and feedback analysis based on uncertain preferences mathematical model is presented. To deal with an uncertain model, three different ranking criteria are being used to develop: a) Expected value, b) Optimistic value, c) Dependent optimistic value criterion. These mathematical models are transformed into their corresponding deterministic forms using the basic concepts of uncertainty theory. The deterministic model of DOCM consists of fractional objectives which are converted into their linear form using Charnes and Cooper's transformation. These deterministic formulations MOFCAP are converted into a single objective problem by using the fuzzy programming technique with linear and exponential membership functions. Further, the single objective problem for all the defined models is solved in the Lingo 18.0 software to derive the Pareto-optimal solution. The sensitivity of the models is also performed to examine the variation in the objective function due to the variation in parameters. Finally, a numerical example is given to exhibit the application and algorithm of the models.

关键词： University course scheduling 0-1 integer programming Uncertainty theory Fractional programming fuzzy programming approach

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