Metaheuristic Routing: A Taxonomy and Energy-Efficient Framework for Internet of Things

Rana, Bharti; Singh, Yashwant; Singh, Harvinder

doi:10.1109/access.2021.3128814

Cited by 10 publications

(1 citation statement)

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“…Since D-PFA was developed to solve symmetric TSP, more study is necessary to establish D-PFA's in tackling constraints like greenness [73] and time frames [74] for efficient large-scale problem solving. Future research can also focus on adapting the proposed D-PFA to solve different discrete optimization problems and comparing it to other methodologies that solve real-world problems, such as the VRP [75][76][77] allocation and scheduling in cloud computing [78,79], internet of things [80], open shop [66,81], and other scheduling and routing problems, to demonstrate its efficiency and effectiveness in other engineering problems.…”

Section: Discussionmentioning

confidence: 99%

D-PFA: A Discrete Metaheuristic Method for Solving Traveling Salesman Problem Using Pathfinder Algorithm

Pirozmand,

Hosseinabadi,

Chari

et al. 2023

IEEE Access

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The Traveling Salesman Problem (TSP) which is a theoretical computer science and operations research problem, has several applications even in its purest formulation, such as the manufacture of microchips, planning, and logistics. There are many methods proposed in the literature to solve TSP with gains and losses. We propose a discrete metaheuristic method called D-PFA to solve this problem more efficiently. Initially, the Pathfinder Algorithm (PFA) was presented to handle issues involving continuous optimization, where it worked effectively. In recent years, there have been various published variants of PFA, and it has been frequently employed to address engineering challenges. In this study, the original PFA algorithm is broken into four subalgorithms and every sub-algorithm is discretized and coupled to form a new algorithm. The proposed algorithm has a high degree of flexibility, a quick response time, strong exploration and exploitation. To validate the significant advantages of the proposed D-PFA, 34 different instances with different sizes are used in simulation results. The proposed method was also compared with 12 State-of-the-Art algorithms. Results indicate that the suggested approach is more competitive and resilient in solving TSP than other algorithms in different aspects. A conclusion and an outlook on future studies and applications are given at the end of the paper.

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