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Souhail Dhouib
University of Sfax
Electrical & Electronics Engineering

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Solving the trapezoidal fuzzy assignment problem using the novel Dhouib-Matrix-AP1 heuristic Souhail Dhouib; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4855

Abstract

The assignment problem is a famous problem in combinatorial optimization where several objects (tasks) are assigned to different entities (workers) with the goal of minimizing the total assignment cost. In real life, this problem often arises in many practical applications with uncertain data. Hence, this data (the assignment cost) is usually presented as fuzzy numbers. In this paper, the assignment problem is considered with trapezoidal fuzzy parameters and solved using the novel Dhouib-Matrix-AP1 (DM-AP1) heuristic. In fact, this research work presents the first application of the DM-AP1 heuristic to the fuzzy assignment problem, and a step-by-step application of DM-AP1 is detailed for more clarity. DM-AP1 is composed of three simple steps and repeated only once in n iterations. Moreover, DM-AP1 is enhanced with two techniques: a ranking function to order the trapezoidal fuzzy numbers and the min descriptive statistical metric to navigate through the research space. DM-AP1 is developed under the Python programming language and generates a convivial assignment network diagram plan.
Comparing the novel Dhouib-Matrix-SPP to genetic algorithm for autonomous mobile robot path planning problem Souhail Dhouib; Danijela Pezer; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.11712

Abstract

Autonomous mobile robots (AMRs) are becoming integral to applications ranging from industrial automation to urban mobility. A core challenge in deploying AMRs effectively is the path planning problem determining an optimal and collision-free path from a start to a goal location within a given environment. This paper proposes a novel method, Dhouib-Matrix-SPP (DM-SPP), that enhances path planning efficiency and adaptability for AMRs operating in different statistical environment. Basically, DM-SPP is developed to unravel the shortest path in a graph and based on columns-rows structure with polynomial computational time. Here, the DM-SPP method is adapted to plan the shortest feasible path between two positions while avoiding obstacles. In order to prove the validity of the proposed DM-SPP method, it is applied to different environments and compared to different case studies taken from the literature. The simulation results show that the DM-SPP method was able to find, with a significantly lower number of iterations, the optimal solutions in comparison with other results obtained by the genetic algorithm (GA) method. DM-SPP presents an overall average improvement in computation time of (37882.55%) compared to the GA, which can reduce search and execution time.
Co-Authors Danijela Pezer Tole Sutikno