Fractional two-stage transshipment problem under uncertainty: application of the extension principle approach

Garg, Harish; Mahmoodirad, Ali; Niroomand, Sadegh

doi:10.1007/s40747-020-00236-2

Cited by 8 publications

(4 citation statements)

References 40 publications

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“…The technique demonstrated computational efficiency and applicability to a wide range of transshipment problems, supported by numerical illustrations. Garg et al [10] investigated a fuzzy fractional two-stage transshipment problem, using the ratio of costs divided by benefits as the objective function. They employed the extension principle and Charnes-Cooper transformation method to find the fuzzy objective value.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The distance between emperor penguins and the best penguin can be calculated using two vectors that prevent collision 𝐴 ⃗ and 𝐶 ⃗ , the position of the penguin 𝑖 in the current iteration (𝑃 𝐼𝑡𝑟 (𝑖)), a social force 𝑆, and the position of the current optimal emperor penguin (𝑃 𝑜𝑝𝑡 ). The proposed equation by Dhiman and Kumar [15] to calculate the distance (𝐷) is presented in equation (10). The calculations of the two collision vectors 𝐴 ⃗ and 𝐶 ⃗ are shown in equations ( 11) and (12), respectively.…”

Section: Determining the Distance Between The Emperor Penguinsmentioning

confidence: 99%

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A Modified Emperor Penguin Optimizer Algorithm for Solving Fixed-Charged Transshipment Problem

Eltoukhy,

Zakaraia

2024

IJCAI

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This paper introduces a novel optimization problem termed the Fixed Charged Transshipment Problem (FCTP), which incorporates fixed charges for selected routes. A new formulation for this problem is presented, aiming to address the combinatorial nature of the challenge. The study further introduces a Modified Emperor Penguin Optimizer (EPO) algorithm designed to enhance the solution approach. To evaluate the performance of the Modified EPO, a comparative analysis is conducted against the classical EPO and Particle Swarm Optimization (PSO) algorithms. 19 problems, including various multi-modal test optimization functions, serve as the testing ground. Results demonstrate the efficacy of the Modified EPO, establishing its superiority over the classical EPO and PSO. Additionally, a heuristic procedure is proposed for solving the combinatorial aspect of the FCTP. This heuristic is hybridized with both the Modified EPO and PSO algorithms. 30 FCTP problems are generated using a code available at https://github.com/MZakaraia/EPO_Transshipment/. Taguchi's orthogonal arrays are employed to optimize parameter levels for both algorithms. The study concludes with the comparison of the Modified Hybrid EPO and Hybrid PSO in solving the 30 generated FCTP problems. Remarkably, the Modified Hybrid EPO algorithm outperforms the Hybrid PSO, showing its effectiveness in addressing the Fixed Charged Transshipment Problem in terms of means and robustness.Povzetek: Članek predstavlja spremenjeni algoritem cesarskega pingvina za reševanje problema s fiksnimi stroški prenosa, ki kaže premoč nad klasičnimi metodami z robustnostjo in učinkovitostjo rešitev.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Determining the Distance Between The Emperor Penguinsmentioning

confidence: 99%

A Modified Emperor Penguin Optimizer Algorithm for Solving Fixed-Charged Transshipment Problem

Eltoukhy,

Zakaraia

2024

IJCAI

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“…The literature is consisted of several innovative concepts for the prediction of the vehicles' trajectories or the determination of the drivers' conditions, for instance, whether they are drunk [19]. There several instances for the IoV technologies, for example, edge/cloud computing [20][21][22], blockchain [23,24], sensor technologies [25], artificial intelligence (AI) [26][27][28][29][30] etc. These technologies are capable of exploring the most proper solutions required for providing reliability, security, and autonomy for vehicular networks [1].…”

Section: Internet Of Vehiclesmentioning

confidence: 99%

ASATM: Automated security assistant of threat models in intelligent transportation systems

Ramazanzadeh

Barzegar

Motameni

2022

IET Computers & Digital Tech

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The evolution of technology has led to the appearance of smart cities. An essential element in such cities is smart mobility that covers the subjects related to Intelligent Transportation Systems (ITS). The problem is that the ITS vulnerabilities may considerably harm the life quality and safety status of human beings living in smart cities. In fact, software and hardware systems are more exposed to security risks and threats. To reduce threats and secure software design, threat modelling has been proposed as a preventive solution in the software design phase. On the other hand, threat modelling is always criticised for being time consuming, complex, difficult, and error prone. The approach proposed in this study, that is, Automated Security Assistant of Threat Models (ASATM), is an automated solution that is capable of achieving a high level of security assurance. By defining concepts and conceptual modelling as well as implementing automated security assistant algorithms, ASATM introduces a new approach to identifying threats, extracting security requirements, and designing secure software. The proposed approach demonstrates a quantitative classification of security at three levels (insecure, secure, and threat), twelve sub‐levels (nominal scale and colour scale), and a five‐layer depth (human understandability and conditional probability). In this study, to evaluate the effectiveness of our approach, an example with various security parameters and scenarios was tested and the results confirmed the superiority of the proposed approach over the latest threat modelling approaches in terms of method, learning, and model understanding.

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“…were demonstrated. More recently; [26] addressed a solid transportation problem with interval cost by the use of fractional goal programming method; [37] developed a framework of bi-level MOLFPP to optimize water consumption structure; [1] investigated the fractional-order tumour-immune-vitamin model trough fixed point results; [12] presented an application of the LFPP with fuzzy nature in industry sector; [33,34] developed the application of multi-objective controllers in medical science and industry; [21] transformed a set covering problem, which has application in the real world problems such as facility problems, airlines schedules problem, etc., into the MOLFPP; [17] studied a fractional two-stage transshipment problem where all the parameters are represented by fuzzy numbers; [16] presented a multiobjective linear fractional inventory problem with generalized intuitionistic fuzzy numbers.…”

mentioning

confidence: 99%

A new efficient approach to tackle multi objective linear fractional problem with flexible constraints

Borza

Rambely²

2023

JIMO

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<p style='text-indent:20px;'>Finding efficient solutions for the multi-objective linear fractional programming problem (MOLFPP) is a challenging issue in optimization due to the fact that more than one objective must be taken into consideration by the decision maker. For this class of optimization problems, we deal with the concept of efficient solutions. The set of efficient solutions could be an infinite set especially when the objectives are in conflict. In this paper, we present a new methodology to address the MOLFPP with flexible constraints i.e. the constraints with fuzzy right hand sides. In the method, firstly, the concept of the <inline-formula><tex-math id="M1">\begin{document}$ \alpha- $\end{document}</tex-math></inline-formula>cuts and ranking of fuzzy numbers are utilized to transform the original problem into the MOLFPP with fixed right hand sides. Secondly, a new MOLFPP is constructed based on the membership functions of the objectives. Afterward this new problem is changed into a single objective programming problem using the weighted sum approach. Finally, the global optimal solution of this single objective programming is obtained by taking into account a finite number of linear programming problems (LPPs). It is proven that the obtained solution is efficient for the main problem. Numerical examples are given to illustrate the method and comparisons are made to show the accuracy.</p>

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Fractional two-stage transshipment problem under uncertainty: application of the extension principle approach

Cited by 8 publications

References 40 publications

A Modified Emperor Penguin Optimizer Algorithm for Solving Fixed-Charged Transshipment Problem

A Modified Emperor Penguin Optimizer Algorithm for Solving Fixed-Charged Transshipment Problem

ASATM: Automated security assistant of threat models in intelligent transportation systems

A new efficient approach to tackle multi objective linear fractional problem with flexible constraints

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