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Improved Whale Optimization Algorithm and Its Application to UCAV Path Planning Problem

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Genetic and Evolutionary Computing (ICGEC 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 834))

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Abstract

This study proposes an improved whale optimization algorithm (WOA), termed improved WOA, by proposing a new judgment criterion for selecting the process of encircling prey or searching for prey in the WOA. The new judgment criterion is a self-tuning parameter that is based on the quality of agent’s fitness instead of a random value used in the original WOA. The agent with higher fitness, i.e., superior agent, updates its position towards the best agent found so far. On the contrary, the agent with lower fitness, i.e., inferior agent, updates its position toward a reference agent which is selected randomly from the population. The performance of the proposed WOA is examined by testing six benchmark functions on low, medium, and high dimensions. Furthermore, the proposed WOA is applied to the path planning of unmanned combat aerial vehicle (UCAV). The computed results of flight path and optimal cost obtained using the improved WOA will be compared with those obtained using the original WOA.

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Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, 350118, Fujian, China

    Jeng-Shyang Pan

  2. Department of Information Management, I-Shou University, Kaohsiung, 84001, Taiwan

    Jenn-Long Liu

  3. Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, 30013, Taiwan

    En-Jui Liu

Authors
  1. Jeng-Shyang Pan
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  2. Jenn-Long Liu
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  3. En-Jui Liu
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Corresponding author

Correspondence to Jenn-Long Liu .

Editor information

Editors and Affiliations

  1. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. Department of Computing, Mathematics, and Physics, Western Norway University of Applied Sciences, Bergen, China

    Jerry Chun-Wei Lin

  3. Changzhou College of Information Technology, Changzhou, Jiangsu, China

    Bixia Sui

  4. College of Smart Living and Management, Tajen University, Pingtung, Taiwan

    Shih-Pang Tseng

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Pan, JS., Liu, JL., Liu, EJ. (2019). Improved Whale Optimization Algorithm and Its Application to UCAV Path Planning Problem. In: Pan, JS., Lin, JW., Sui, B., Tseng, SP. (eds) Genetic and Evolutionary Computing. ICGEC 2018. Advances in Intelligent Systems and Computing, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-5841-8_5

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