Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Decision support system using Dhouib-Matrix-TP1 heuristic for pentagonal fuzzy transportation problem
View through CrossRef
In this paper, a decision support system (DSS) is provided to assist the decision-maker in obtaining the best solution for the transportation problem under uncertainty. Fuzzy parameters of the transportation problem are presented by pentagonal fuzzy numbers. The centroid ranking function transforms these pentagonal fuzzy numbers into crisp ones. Then, a novel, improved greedy method named Dhouib-Matrix-TP1 (DM-TP1) is used in order to help the decision-maker promptly find a suitable solution. Specifically, this DSS is composed of three components: the data base component considers a pentagonal fuzzy number; the Model Base component thinks through the original heuristic DM-TP1; and the User Interface component deliberates the convivial graphical output of the generated transportation plan solution using the Python programming language. Experiments in the literature on fuzzy transportation problems show that the novel proposed heuristic, DM-TP1, is easy to understand and allows the decision-maker to handle transportation problems under pentagonal fuzzy numbers. Also, the DM-TP1 is robust and can be applied to find a feasible initial solution in less time.
Institute of Advanced Engineering and Science
Title: Decision support system using Dhouib-Matrix-TP1 heuristic for pentagonal fuzzy transportation problem
Description:
In this paper, a decision support system (DSS) is provided to assist the decision-maker in obtaining the best solution for the transportation problem under uncertainty.
Fuzzy parameters of the transportation problem are presented by pentagonal fuzzy numbers.
The centroid ranking function transforms these pentagonal fuzzy numbers into crisp ones.
Then, a novel, improved greedy method named Dhouib-Matrix-TP1 (DM-TP1) is used in order to help the decision-maker promptly find a suitable solution.
Specifically, this DSS is composed of three components: the data base component considers a pentagonal fuzzy number; the Model Base component thinks through the original heuristic DM-TP1; and the User Interface component deliberates the convivial graphical output of the generated transportation plan solution using the Python programming language.
Experiments in the literature on fuzzy transportation problems show that the novel proposed heuristic, DM-TP1, is easy to understand and allows the decision-maker to handle transportation problems under pentagonal fuzzy numbers.
Also, the DM-TP1 is robust and can be applied to find a feasible initial solution in less time.
Related Results
619. Pharmacokinetic-Pharmacodynamic (PK-PD) Target Attainment Analyses to Support Epetraborole Dose Selection for the Treatment of Patients with Mycobacterium avium Complex (MAC) Lung Disease
619. Pharmacokinetic-Pharmacodynamic (PK-PD) Target Attainment Analyses to Support Epetraborole Dose Selection for the Treatment of Patients with Mycobacterium avium Complex (MAC) Lung Disease
Abstract
Background
Epetraborole (EBO) is an orally available, bacterial leucyl transfer RNA synthetase inhibitor that concentra...
LB2306. Population Pharmacokinetic (PPK), Pharmacokinetic/Pharmacodynamic attainment (PTA), and Clinical Pharmacokinetic/Pharmacodynamic (PK/PD) Analyses for Sulbactam-Durlobactam (SUL-DUR) to Support Dose Selection for the Treatment of Acinetobacter baum
LB2306. Population Pharmacokinetic (PPK), Pharmacokinetic/Pharmacodynamic attainment (PTA), and Clinical Pharmacokinetic/Pharmacodynamic (PK/PD) Analyses for Sulbactam-Durlobactam (SUL-DUR) to Support Dose Selection for the Treatment of Acinetobacter baum
Abstract
Background
SUL-DUR is a β-lactam/β-lactamase inhibitor combination in development for the treatment of ABC infections, ...
593. Population Pharmacokinetic Model Development for Epetraborole and Mycobacterium avium Complex (MAC) Lung Disease Patients Using Data from Phase 1 and 2 Studies
593. Population Pharmacokinetic Model Development for Epetraborole and Mycobacterium avium Complex (MAC) Lung Disease Patients Using Data from Phase 1 and 2 Studies
Abstract
Background
Epetraborole (EBO), an orally available bacterial leucyl transfer RNA synthetase inhibitor with potent activ...
592. Impact of Elevated MIC Values on Echinocandin Pharmacokinetic-Pharmacodynamic (PK-PD) Candida glabrata Target Attainment (TA)
592. Impact of Elevated MIC Values on Echinocandin Pharmacokinetic-Pharmacodynamic (PK-PD) Candida glabrata Target Attainment (TA)
Abstract
Background
Given the increasing prevalence of non-albicans Candida species, including C. glabrata and C. auris, which h...
Supply Chain Networks Optimization under Uncertain Environment with Dhouib-Matrix-TP1 heuristic
Supply Chain Networks Optimization under Uncertain Environment with Dhouib-Matrix-TP1 heuristic
The transportation problem (TP) is a critical component of the supply chain network that involves determining the most efficient way to move goods from one location to another. TP ...
Solving the Trapezoidal Fuzzy Transportation Problems via New Heuristic
Solving the Trapezoidal Fuzzy Transportation Problems via New Heuristic
The transportation problem is a one of the principal topics in operational research where goods are initially stored at different sources and need to be livered to destination in s...
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Abstract. Fuzzy Inference System requires several stages to get the output, 1) formation of fuzzy sets, 2) formation of rules, 3) application of implication functions, 4) compositi...
Neutrosophic Triangular Fuzzy Travelling Salesman Problem Based on Dhouib-Matrix-TSP1 Heuristic
Neutrosophic Triangular Fuzzy Travelling Salesman Problem Based on Dhouib-Matrix-TSP1 Heuristic
In this paper, the Travelling Salesman Problem is considered in neutrosophic environment which is more realistic in real-world industries. In fact, the distances between cities in ...