FL-MTSP: a fuzzy logic approach to solve the multi-objective multiple traveling salesman problem for multi-robot systems

Trigui, Sahar; Cheikhrouhou, Omar; Koubâa, Anis; Baroudi, Uthman; Youssef, Habib

doi:10.1007/s00500-016-2279-7

Cited by 52 publications

(19 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To ensure diversity and convergence, the work [27] presents a strategy to select the leader for each particle. Several metrics are combined into a single fuzzy metric to convert multiple objectives into a single objective in [28].…”

Section: B Multi-objective Optimizationmentioning

confidence: 99%

Particle Swarm Optimization for Cooperative Multi-Robot Task Allocation: A Multi-Objective Approach

Wei

Cai

2020

IEEE Robot. Autom. Lett.

View full text Add to dashboard Cite

show abstract

Section: B Multi-objective Optimizationmentioning

confidence: 99%

Particle Swarm Optimization for Cooperative Multi-Robot Task Allocation: A Multi-Objective Approach

Wei

Cai

2020

IEEE Robot. Autom. Lett.

View full text Add to dashboard Cite

show abstract

“…On the basis of the above method, in [32], Imeson proposes a new method that simplifies the SAT-TSP language to the general TSP language in senior robotic route planning issues. In [33], Trigui takes into account the issue of dispatching object positions visited by mobile robots. In order to solve the above problem, a fuzzy logic algorithm is proposed to settle the multi-target TSP aiming at multiple robot system.…”

Section: Related Workmentioning

confidence: 99%

The Repair Strategy for Event Coverage Holes Based on Mobile Robots in Wireless Sensor and Robot Networks

Zhuang

Wu³

et al. 2019

Sensors

View full text Add to dashboard Cite

In the application of the wireless sensor and robot networks (WSRNs), there is an urgent need to accommodate flexible surveillance tasks in intricate surveillance scenarios. On the condition of flexible surveillance missions and demands, event coverage holes occur in the networks. The conventional network repair methods based on the geometric graph theory such as Voronoi diagram method are unable to meet the conditions of flexible surveillance tasks and severe multi-restraint scenarios. Mobile robots show obvious advantages in terms of adaptation capacity and mobility in hazardous and severe scenarios. First, we propose an event coverage hole healing model for multi-constrained scenarios. Then, we propose a joint event coverage hole repair algorithm (JECHR) on the basis of global repair and local repair to apply mobile robots to heal event coverage holes in WSRNs. Different from conventional healing methods, the proposed algorithm can heal event coverage holes efficaciously which are resulted from changing surveillance demands and scenarios. The JECHR algorithm can provide an optimal repair method, which is able to adapt different kinds of severe multi-constrained circumstances. Finally, a large number of repair simulation experiments verify the performance of the JECHR algorithm which can be adapted to a variety of intricate surveillance tasks and application scenarios.

show abstract

“…Combining MART with fuzzy logic has also witnessed a lot of attention and activities. For example, several metrics are combined into a single fuzzy metric to convert multiple objectives into a single objective in [7]. In [8], multiple robots were deployed to track oil spill on the sea surfaces.…”

Section: Introductionmentioning

confidence: 99%

Multi-robot Task Allocation System: Fuzzy Auction-Based and Adaptive Multi-threshold Approaches

Al-Shaboti

Baroudi

2021

SN COMPUT. SCI.

Self Cite

View full text Add to dashboard Cite

Auction-based and threshold-based are the prevalent approaches for multi-robot distributed task allocation problem. We study the performance of these two approaches under a multi-objective dynamic task allocation scenario. The fuzzy inference system (FIS) is used in the auction-based approach to convert the objectives into a representative bid value. Experiments reveal that FIS auction-based outperforms the adaptive threshold-based approach in terms of load balancing. In contrast, the adaptive threshold-based approach produces better results in terms of traveled distance. Moreover, both approaches can achieve the same quality satisfaction objective.

show abstract

FL-MTSP: a fuzzy logic approach to solve the multi-objective multiple traveling salesman problem for multi-robot systems

Cited by 52 publications

References 25 publications

Particle Swarm Optimization for Cooperative Multi-Robot Task Allocation: A Multi-Objective Approach

Particle Swarm Optimization for Cooperative Multi-Robot Task Allocation: A Multi-Objective Approach

The Repair Strategy for Event Coverage Holes Based on Mobile Robots in Wireless Sensor and Robot Networks

Multi-robot Task Allocation System: Fuzzy Auction-Based and Adaptive Multi-threshold Approaches

Contact Info

Product

Resources

About