Optimizing a GPU-Parallelized Ant Colony Metaheuristic by Parameter Tuning

Borisenko, Andrey; Gorlatch, Sergei

doi:10.1007/978-3-030-25636-4_12

Cited by 4 publications

(1 citation statement)

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“…The ACO is a probabilistic technique that bio-mimics the behavior of ants and the process of searching foods by searching the optimal path route to solve the complex optimization problem [227]. Implementing the ACO algorithm for solving the path optimization problems has several advantages, such as strong robustness [228,229] and parallel computation [230,231]. However, the algorithm could easily trap in the local optimum as well as slow convergence speed [232,233].…”

Section: ) Swarm Intelligencementioning

confidence: 99%

A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms

Mohd‐Mokhtar²,

2021

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The small battery capacities of the mobile robot and the un-optimized planning efficiency of the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in terms of speed and accuracy, putting a great constraint on the usability of the robot applications in various planning strategies in specific environmental conditions. Thus, it became highly desirable to address the optimization problems related to exploration and coverage path planning (CPP). In general, the goal of the CPP is to find an optimal coverage path with generates a collision-free trajectory by reducing the travel time, processing speed, cost energy, and the number of turns along the path length, as well as low overlapped rate, which reflect the robustness of CPP. This paper reviews the principle of CPP and discusses the development trend, including design variations and the characteristic of optimization algorithms, such as classical, heuristic, and most recent deep learning methods. Then, we compare the advantages and disadvantages of the existing CPP-based modeling in the area and target coverage. Finally, we conclude numerous open research problems of the CPP and make suggestions for future research directions to gain insights. INDEX TERMSCoverage path planning, exploration, heuristic algorithm, deep reinforcement learning.

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Section: ) Swarm Intelligencementioning

confidence: 99%

A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms

Mohd‐Mokhtar²,

2021

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Information system for decision-making support with resources allocation between geographically remote objects within a production association

Salih

Egorov

Nemtinova

et al. 2020

J. Phys.: Conf. Ser.

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In this article, we discuss the issues of creating an information system for decision-making support for the task of resources rationing at geographically remote objects within a production association. The article contains the problem statement and the algorithm for solving the problem of redistributing quotas for production resources between separate remote objects (structural divisions) of a production association, settlement of payments between them, which allow reducing total costs for the entire association.

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