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Unravelling the assignment problem under intuitionistic triangular fuzzy environment by the novel heuristic Dhouib-Matrix-AP1 用新颖的启发式Dhouib-Matrix-AP1揭示直觉三角模糊环境下的分配问题
Q3 Decision Sciences Pub Date : 2023-01-01 DOI: 10.2298/yjor220915005d
S. Dhouib
The Assignment Problem (AP) can be stated as n activities to be assigned to n resources in such a way that the overall cost of assignment is minimized and each activity is assigned to one and only one resource. In real-life, the parameters of the AP are presented as uncertain numbers due to the lack of knowledge, experiences or any other (internal or external) factor. In this paper, the AP is considered under intuitionistic triangular fuzzy number and solved by the novel constructive heuristic Dhouib-Matrix-AP1 (DM-AP1) with a time complexity of O(n). Actually, this paper presents the first enhancement of the novel heuristic DM-AP1 to solve the AP under intuitionistic triangular fuzzy environment. DM-AP1 is composed of three simple steps: computing the total cost, selecting the highest value and finding the minimal element. These steps are repeated in n iterations with the use of a standard deviation statistical metric. Two case studies of AP under intuitionistic triangular fuzzy set are taken from the literature and a step-by-step application of the novel DM-AP1 heuristic is presented for more clarification.
分配问题(AP)可以描述为将n个活动分配给n个资源,这样分配的总成本最小,并且每个活动分配给一个且只有一个资源。在现实生活中,由于缺乏知识、经验或任何其他(内部或外部)因素,AP的参数呈现为不确定的数字。本文考虑直觉三角模糊数下的AP问题,采用时间复杂度为0 (n)的新型建设性启发式Dhouib-Matrix-AP1 (DM-AP1)求解。实际上,本文首次对启发式算法DM-AP1进行了改进,解决了直觉三角模糊环境下的AP问题。DM-AP1由三个简单步骤组成:计算总成本、选择最大值和寻找最小元素。这些步骤在使用标准偏差统计度量的n次迭代中重复。本文从文献中选取了直觉三角模糊集下AP的两个案例研究,并给出了新的DM-AP1启发式的逐步应用。
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引用次数: 4
A pythagorean hesitant fuzzy programming approach and its application to multi objective reliability optimization problem 毕达哥拉斯犹豫模糊规划方法及其在多目标可靠性优化问题中的应用
Q3 Decision Sciences Pub Date : 2023-01-01 DOI: 10.2298/yjor230417024j
Swarup Jana, Sahidul Islam
Decision-making problems can often be effectively solved using traditional optimization methods that have a clearly defined configuration. However, in real-world scenarios, decision-makers frequently encounter doubt or hesitation, making it challenging to precisely specify certain parameters. As a result, they often seek input from different experts, leading to conflicting values and varying levels of satisfaction among decision-makers. This uncertainty and lack of crisp values make decision-making problems inherently non-deterministic. In this paper, a novel Pythagorean hesitant fuzzy (PHF) programming method is designed to address the challenges of optimization problems with multiple objectives. Here PHF aggregation operators are used to aggregate the PHF memberships and non-memberships of the objectives. Additionally, to account the uncertainties of the parameters of the optimization problem Parabolic Pythagorean fuzzy number is used and centroid method is applied for defuzzification. We solved an example of multi objective optimization problem of manufacturing system to demonstrate our proposed method and finally, presented a case study on reliability optimization model for Life Support Systems, where the primary objectives are to maximize system reliability and minimize cost. The result is compared with other existing methods by degree of closeness.
使用具有明确定义的配置的传统优化方法通常可以有效地解决决策问题。然而,在现实场景中,决策者经常会遇到怀疑或犹豫,这使得精确指定某些参数变得具有挑战性。因此,他们经常寻求不同专家的意见,导致价值观冲突和决策者满意度的不同。这种不确定性和缺乏清晰的价值观使得决策问题本质上是非确定性的。针对多目标优化问题的挑战,提出了一种新的毕达哥拉斯犹豫模糊规划方法。这里,PHF聚合操作符用于聚合目标的PHF成员和非成员关系。此外,考虑到优化问题参数的不确定性,采用抛物线毕达哥拉斯模糊数,并采用质心法进行去模糊化。以制造系统多目标优化问题为例,给出了以系统可靠性最大化和成本最小化为主要目标的生命保障系统可靠性优化模型。并将所得结果与现有方法的接近度进行了比较。
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引用次数: 0
An EPQ model for delay deteriorating products with price, freshness and greening efforts dependent demand under markdown strategy 降价策略下价格、新鲜度和环保程度依赖于需求的延迟变质产品EPQ模型
Q3 Decision Sciences Pub Date : 2023-01-01 DOI: 10.2298/yjor230515023k
Dharmesh Katariya, Kunal Shukla
Consumers today use green, fresh, perishable products because of their freshness, healthfulness, and sustainability. In this article, we developed the continuous production inventory model for the producer who produces and sells fresh perishable products with the input of green efforts. There are two distinct kinds of product decay to take into account: products whose physical condition gradually deteriorates over time at a constant rate, and products whose freshness quality declines with time. Product demand is influenced by the selling price of the product, its freshness level, and its greening efforts. In order to increase the sales of inventory and enhance the profit from clearing stocks at the end of their life, we have adopted the markdown policy. Due to freshness degradation, a markdown strategy is adopted after a period of product deterioration to boost demand. The objectives of the study are to find out the optimal period for replenishment cycle time, the optimal value of greening efforts, and the optimal markdown percentage such that the producer?s total profit is maximum. A numerical example is used to validate a mathematical formulation that reflects real-world circumstances. A sensitivity analysis of the parameters is done to determine the model's reliability. Some significant managerial results are provided, and the article concludes with a consideration of the future scope of related research.
今天的消费者使用绿色、新鲜、易腐烂的产品,因为它们的新鲜、健康和可持续性。本文建立了以绿色努力为投入,生产和销售新鲜易腐产品的生产者的连续生产库存模型。有两种不同的产品腐烂需要考虑:一种是物理状况随时间以恒定速率逐渐恶化的产品,另一种是新鲜度随时间下降的产品。产品需求受产品的销售价格、新鲜度和绿化程度的影响。为了增加存货的销售,提高存货到期清算的利润,我们采取了降价政策。由于新鲜度下降,在产品变质一段时间后采取降价策略以刺激需求。研究的目的是找出最优的补货周期时间,最优的绿化努力值,以及最优的降价百分比,使生产商?总利润是最大的。用一个数值例子来验证反映现实世界情况的数学公式。通过对参数的敏感性分析,确定了模型的可靠性。文章最后给出了一些重要的管理成果,并对未来相关研究的范围进行了展望。
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引用次数: 0
Effect of green technology investment on crude oil inventory system - a case study based on ONGC data 绿色技术投资对原油库存系统的影响——以印度石油天然气公司为例
Q3 Decision Sciences Pub Date : 2023-01-01 DOI: 10.2298/yjor230415025s
Abhibasu Sen, Karabi Dutta Choudhury, Tapan Datta
The carbon footprints are increasing in the environment at an alarming rate mainly due to unplanned human activities. The world?s population will continue to grow at a rapid pace in the future. As a result, our future generations may find it difficult to live on this planet in a healthy manner. The world?s developed and developing countries began to investigate various methods for reducing their carbon footprint. However, it will not be sustainable if it is also not economically viable. In this scenario, maintaining a good profit for businesses while reducing their carbon footprint necessitates a pragmatic strategy. In this article, we will try to find a way out that will provide us with a practical solution. We will simulate the profitability of an upstream oil manufacturer that has invested heavily in green technologies. Under a carbon tax system, we will use the production-inventory model. This system assumes that capital investment in green technology can reduce emissions, and increase profits. We used data from the Oil and Natural Gas Corporation of India, available in its annual reports. As a matter of fact, the Oil and Natural Gas Corporation of India accounts for 70% of crude oil production in India and is a major player in India?s upstream oil companies. The results were quite encouraging, with deviations between expected and actual values being less than 10%. 2 Sen, Dutta Choudhury and Datta / Effect of Green Technology The findings also led us to believe that the excise duty and the pollution control tax levied in India can be regarded as a Green Tax or Carbon Tax. We used a published research model to find the optimal solution.
环境中的碳足迹正以惊人的速度增长,这主要是由于计划外的人类活动。世界吗?未来,美国人口将继续快速增长。因此,我们的后代可能会发现很难以健康的方式生活在这个星球上。世界吗?发达国家和发展中国家开始研究各种减少碳足迹的方法。然而,如果它在经济上也不可行,它将是不可持续的。在这种情况下,为企业保持良好的利润,同时减少碳足迹,需要一个务实的战略。在本文中,我们将尝试找到一条能为我们提供实际解决方案的出路。我们将模拟上游石油制造商在绿色技术上投入巨资的盈利能力。在碳税制度下,我们将使用生产-库存模型。这一体系假定对绿色技术的资本投资可以减少排放,增加利润。我们使用的数据来自印度石油和天然气公司的年度报告。事实上,印度石油天然气公司(Oil and Natural Gas Corporation of India)占印度原油产量的70%,是印度的主要参与者。美国上游石油公司。结果非常令人鼓舞,期望值和实际值之间的偏差小于10%。2 Sen, Dutta Choudhury和Datta /绿色技术的影响研究结果还使我们相信印度征收的消费税和污染控制税可以被视为绿色税或碳税。我们使用已发表的研究模型来寻找最优解。
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引用次数: 0
Bounds on eigenvalues of real symmetric interval matrices for αBB method in global optimization αBB方法全局寻优实数对称区间矩阵的特征值界
Q3 Decision Sciences Pub Date : 2023-01-01 DOI: 10.2298/yjor230315019z
Djamel Zerrouki, Mohand Ouanes
In this paper, we investigate bounds on eigenvalues of real symmetric interval matrices. We present a method that computes bounds on eigenvalues of real symmetric interval matrices. It outperforms many methods developed in the literature and produces as sharp as possible bounds on eigenvalues of real symmetric interval matrices. The aim is to apply the proposed method to compute lower bounds on eigenvalues of a symmetric interval hessian matrix of a nonconvex function in the ?BB method and use them to produce a tighter underestimator that improves the ?BB algorithm for solving global optimization problems. In the end, we illustrate by example, the comparison of various approaches of bounding eigenvalues of real symmetric interval matrices. Moreover, a set of test problems found in the literature are solved efficiently and the performances of the proposed method are compared with those of other methods.
本文研究了实对称区间矩阵的特征值界。给出了一种计算实对称区间矩阵特征值界的方法。它优于文献中开发的许多方法,并在实对称区间矩阵的特征值上产生尽可能清晰的界。目的是应用所提出的方法计算非凸函数的对称区间hessian矩阵的特征值下界,并利用它们产生一个更紧密的低估量,从而改进了求解全局优化问题的BB算法。最后,我们用实例说明了实对称区间矩阵边界特征值的各种方法的比较。此外,有效地解决了文献中发现的一组测试问题,并将该方法的性能与其他方法进行了比较。
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引用次数: 0
Multi-fractional fuzzy programming for sustainable agricultural multi-cropping bi-seasonal planning 可持续农业多季复种规划的多分式模糊规划
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.2298/yjor220516026m
Umar Muhammad Modibbo
The agricultural production system composes of several conflicting resources that must be combined to yield the desired product output. However, some goals are not conflicting in the system; therefore, this study presents a multi-objective optimization problem using a multi-fractional fuzzy programming concept. The objective is to optimize the profit ratio to cash expenditure and production of crops in different seasons under the restriction of fertilizer, machine, manpower, water consumption, and land utilization. The proposed model is illustrated with numerical examples for validation from an agrirean village in northern Nigeria. The result shows meaningful achievements and improvement in six crops out of the seven crops for both the dry and rainy seasons. Thus the concept is recommended for decision-makers for proper planning and productive yield in the agricultural industry for ensuring food security and the global sustainable developments.
农业生产系统由几种相互冲突的资源组成,这些资源必须结合起来才能产生期望的产品产出。然而,有些目标在系统中并不冲突;因此,本研究利用多分式模糊规划的概念提出了一个多目标优化问题。目标是在化肥、机器、人力、水消耗和土地利用的限制下,优化作物在不同季节的利润与现金支出和产量的比率。通过尼日利亚北部一个农村的数值算例对所提出的模型进行了验证。结果表明,7种作物中有6种在旱季和雨季都取得了有意义的成果和改善。因此,建议决策者对农业工业进行适当规划和生产,以确保粮食安全和全球可持续发展。
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引用次数: 0
Reliability optimization using hybrid genetic and particle swarm optimization algorithm 基于混合遗传和粒子群算法的可靠性优化
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.2298/yjor220316020d
Tripti Dahiya, D. Garg
Redundancy-allocation problem i.e. RAP is among the reliability optimization problems which make use of non-linear programming method to improve the reliability of complex system. The objective of this research paper is reliability optimization through the application of Genetic Algorithm i.e. GA and Hybrid Genetic & Particle Swarm Optimization (H-GAPSO) on a RAP. Certain shortcomings have been seen when results are obtained by application of single algorithms. In order to get rid of these shortcomings, HGA-PSO is introduced where attractive properties of GA and PSO are combined. This hybrid method makes use of iterative process of GA after obtaining initial best population from PSO. Comparative Analysis of results of GA and H-GAPSO is done with respect to reliability and computation (CPU) time and it is observed that H-GAPSO improved system reliability up to maximum by 63.10%. MATLprogramming has been used for computation of results from GA and HGA-PSO algorithms.
冗余分配问题(RAP)是利用非线性规划方法提高复杂系统可靠性的可靠性优化问题之一。本文的研究目标是通过遗传算法(GA)和混合遗传与粒子群算法(H-GAPSO)在RAP上的应用进行可靠性优化。应用单一算法得到的结果存在一定的缺陷。为了克服这些缺点,将遗传算法和粒子群算法的优点结合起来,引入了遗传算法-粒子群算法。该混合方法利用遗传算法从粒子群中得到初始最优种群后的迭代过程。通过对遗传算法和H-GAPSO算法在可靠性和计算时间方面的比较分析,发现H-GAPSO算法最大可提高系统可靠性63.10%。用matlab编程对遗传算法和HGA-PSO算法的结果进行了计算。
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引用次数: 2
Necessary and sufficient optimality conditions for fractional interval-valued variational problems 分数阶区间值变分问题的充分最优性必要条件
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.2298/yjor210815028r
Vivekananda Rayanki, K. Kummari
In this paper a special kind of variational programming problem involving fractional interval-valued objective function is considered. For such type of problem, insights into LU optimal solutions have been discussed. Using the LU optimal concept, we established optimality conditions for the considered problem. Further, We formulated a Mond-Weir dual problem and discussed appropriate duality theorems for the relationship between dual and primal problems.
本文研究一类特殊的涉及分数阶区间值目标函数的变分规划问题。对于这种类型的问题,已经讨论了LU最优解的见解。利用LU最优概念,建立了所考虑问题的最优性条件。进一步,我们构造了一个Mond-Weir对偶问题,并讨论了对偶问题与原始问题之间关系的对偶定理。
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引用次数: 0
Analysis of bulk service queuing system with rework, unreliable server, resuming service and two kinds of multiple vacation 具有返工、服务器不可靠、恢复服务和两种多重休假的批量服务排队系统分析
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.2298/yjor210719009k
S. Karpagam
In this paper, we discuss a batch arrival bulk service queue with rework for the faculty item, possibility of breakdown, repair, and two kinds of multiple vacation with different threshold policy. The server serves the remaining service after repair completion. This type of queueing model has a lot of applications in the manufacturing/production industries. Performance measures and stability conditions are obtained. Numerical illustrations are made to examine the validity of analytical results.
本文讨论了具有返工、故障可能性、维修可能性和两种不同阈值策略的多假期的批量到达批量服务队列。服务器在修复完成后提供剩余的服务。这种类型的排队模型在制造/生产行业中有很多应用。得到了性能指标和稳定性条件。通过数值算例验证了分析结果的有效性。
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引用次数: 2
1-mean and 1-medoid 2-clustering problem with arbitrary cluster sizes: Complexity and approximation 任意簇大小的1均值和1中位数2聚类问题:复杂性和近似
Q3 Decision Sciences Pub Date : 2022-01-01 DOI: 10.2298/yjor211018008p
A. Pyatkin
We consider the following 2-clustering problem. Given N points in Euclidean space, partition it into two subsets (clusters) so that the sum of squared distances between the elements of the clusters and their centers would be minimum. The center of the first cluster coincides with its centroid (mean) while the center of the second cluster should be chosen from the set of the initial points (medoid). It is known that this problem is NP-hard if the cardinalities of the clusters are given as a part of the input. In this paper we prove that the problem remains NP-hard in the case of arbitrary clusters sizes and suggest a 2-approximation polynomial-time algorithm for this problem.
我们考虑下面的2聚类问题。给定欧几里德空间中的N个点,将其划分为两个子集(聚类),使聚类元素与其中心之间的距离平方和最小。第一个聚类的中心与其质心(均值)重合,而第二个聚类的中心应从初始点(中间点)的集合中选择。众所周知,如果将集群的基数作为输入的一部分给出,则该问题是np困难的。在本文中,我们证明了在任意簇大小的情况下问题仍然是np困难的,并提出了一个2逼近多项式时间算法来解决这个问题。
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引用次数: 1
期刊
Yugoslav Journal of Operations Research
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