The Fitness Landscapes Exploration Based on the Parallel Simulated Annealing Algorithm_Vol. 2 No. 1 (JBDC 2024)_Journal of Big Data and Computing (ISSN: 2959-0590)

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The Fitness Landscapes Exploration Based on the Parallel Simulated Annealing Algorithm

DOI: https://doi.org/10.62517/jbdc.202401114

Author(s)

Shanshan Cui1, Jing Zhao1, Bin Shi2

Affiliation(s)

1College of Information and Computer Engineering, Chuzhou Vocational and Technical College, China 2China Railway Fourth Bureau, China

Abstract

Taken the complexity of managing forests into account, researchers regard the virtual forest environment as an experimental area, and manage the forests efficiently by way of the simulated annealing algorithm. More specifically, this paper evolves the forests from the current forest states to the most desired one using the most efficient path. Due the traditional simulated annealing algorithm converges slowly and has long execution time, this paper takes on a parallel method and its optimization strategy based on simulated annealing. As it is expected, increasing the number of processes is positive in any case; an important supplement to global search is local optimization. All above present that the parallel strategy can be efficient and low cost management of forest landscape.

Keywords

Parallel Algorithm; Simulated Annealing Algorithm; Multiple Markov Chaint

References

[1] Xu Chang;Li Lingchao;Cheng Baodong. "The impact of institutions on forestland transfer rents: The case of Zhejiang province in China."Journal [J] Forest Policy and Economics. Volume 123 , Issue . 2021. [2]Karacan Ismet;Senvar Ozlem;Bulkan Serol. "A Novel Parallel Simulated Annealing Methodology to Solve the No-Wait Flow Shop Scheduling Problem with Earliness and Tardiness Objectives." Journal [J] Processes. Volume 11 , Issue 2 . 2023. PP 454-454. [3]Vuyani Michael Nicholas Dladla;Agha Francis Nnachi;Rembuluwani Philip Tshubwana." Design, Modeling, and Analysis of IEEE Std 80 Earth Grid Design Refinement Methods Using ETAP." Journal [J] Applied Sciences. Volume 13 , Issue 13 . 2023. [4]Arash Mohamadi;Sadoullah Ebrahimnejad;Reza Tavakkoli-Moghaddam."A novel two-stage approach for solving a bi-objective facility layout problem".Journal [J] Int. J. of Operational Research. Volume 31 , Issue 1 . 2018. PP 49-87. [5] Mehdi Rajabzadeh;Abolfazl Toroghi Haghighat." Energy-aware framework with Markov chain-based parallel simulated annealing algorithm for dynamic management of virtual machines in cloud data centers ". Journal [J] The Journal of Supercomputing. Volume 73 , Issue 5 . 2017. PP 2001-2017. [6]Luo Tao;Xie Jianpeng;Zhang Baitao;Zhang Yao;Li Chaoqun;Zhou Jie." An improved levy chaotic particle swarm optimization algorithm for energy-efficient cluster routing scheme in industrial wireless sensor networks ". Journal [J] Building and Environment. Volume 248 , Issue . 2024. [7]Lee Sangmin;Kim Seoung Bum. Parallel Simulated Annealing with a Greedy Algorithm for Bayesian Network Structure Learning. Journal [J] IEEE Transactions on Knowledge and Data Engineering. Volume 32 , Issue 6 . [8] Coll Narcís;Fort Marta;Saus Moisès. Coverage area maximization with parallel simulated annealing Journal [J] Expert Systems With Applications. Volume 202 , Issue . 2022.