A novel hybrid grey wolf optimizer algorithm for unmanned aerial vehicle (UAV) path planning

Abstract Unmanned aerial vehicle (UAV) path planning problem is an important component of UAV mission planning system, which needs to obtain optimal route in the complicated field. To solve this problem, a novel hybrid algorithm called HSGWO-MSOS is proposed by combining simplified grey wolf optimizer (SGWO) and modified symbiotic organisms search (MSOS). In the proposed algorithm, the exploration and exploitation abilities are combined efficiently. The phase of the GWO algorithm is simplified to accelerate the convergence rate and retain the exploration ability of the population. The commensalism phase of the SOS algorithm is modified and synthesized with the GWO to improve the exploitation ability. In addition, the convergence analysis of the proposed HSGWO-MSOS algorithm is presented based on the method of linear difference equation. The cubic B-spline curve is used to smooth the generated flight route and make the planning path be suitable for the UAV. The simulation experimental results show that the HSGWO-MSOS algorithm can acquire a feasible and effective route successfully, and its performance is superior to the GWO, SOS and SA algorithm.

[1]  Y. Volkan Pehlivanoglu,et al.  A new vibrational genetic algorithm enhanced with a Voronoi diagram for path planning of autonomous UAV , 2012 .

[2]  Haibin Duan,et al.  Social-class pigeon-inspired optimization and time stamp segmentation for multi-UAV cooperative path planning , 2018, Neurocomputing.

[3]  Bibhas C. Giri,et al.  Stochastic supply chain model with imperfect production and controllable defective rate , 2018, International Journal of Systems Science: Operations & Logistics.

[4]  Li Zhang,et al.  A scattering and repulsive swarm intelligence algorithm for solving global optimization problems , 2018, Knowl. Based Syst..

[5]  Anjali Awasthi,et al.  A simulation-based optimisation approach for identifying key determinants for sustainable transportation planning , 2018 .

[6]  Jianqiao Yu,et al.  Modified central force optimization (MCFO) algorithm for 3D UAV path planning , 2016, Neurocomputing.

[7]  Tran Hiep Dinh,et al.  Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection , 2017, ArXiv.

[8]  Mahmoud Reza Shakarami,et al.  Wide-area power system stabilizer design based on Grey Wolf Optimization algorithm considering the time delay , 2016 .

[9]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[10]  Yang Liu,et al.  Survey on computational-intelligence-based UAV path planning , 2018, Knowl. Based Syst..

[11]  Zhile Yang,et al.  A novel hybrid teaching learning based multi-objective particle swarm optimization , 2017, Neurocomputing.

[12]  Fang Liu,et al.  Chaotic artificial bee colony approach to Uninhabited Combat Air Vehicle (UCAV) path planning , 2010 .

[13]  Shafii Muhammad Abdulhamid,et al.  Symbiotic Organism Search optimization based task scheduling in cloud computing environment , 2016, Future Gener. Comput. Syst..

[14]  Jiaqiang Zhang,et al.  Reconnaissance Mission Conducted by UAV Swarms Based on Distributed PSO Path Planning Algorithms , 2019, IEEE Access.

[15]  Bijaya K. Panigrahi,et al.  A hybridization of an improved particle swarm optimization and gravitational search algorithm for multi-robot path planning , 2016, Swarm Evol. Comput..

[16]  Wei Pan,et al.  Grey wolf optimizer for unmanned combat aerial vehicle path planning , 2016, Adv. Eng. Softw..

[17]  Qidi Wu,et al.  A survey of biogeography-based optimization , 2017, Neural Computing and Applications.

[18]  Dumitru Baleanu,et al.  A new hybrid algorithm for continuous optimization problem , 2018 .

[19]  B. Giri,et al.  Coordinating a supply chain with backup supplier through buyback contract under supply disruption and uncertain demand , 2014 .

[20]  Seyed Ashkan Hoseini Shekarabi,et al.  An integrated stochastic EPQ model under quality and green policies: generalised cross decomposition under the separability approach , 2019, International Journal of Systems Science: Operations & Logistics.

[21]  Angappa Gunasekaran,et al.  Building theory of sustainable manufacturing using total interpretive structural modelling , 2015 .

[22]  Bibhas C. Giri,et al.  Developing a closed-loop supply chain model with price and quality dependent demand and learning in production in a stochastic environment , 2018, International Journal of Systems Science: Operations & Logistics.

[23]  Chao Deng,et al.  Selective maintenance scheduling under stochastic maintenance quality with multiple maintenance actions , 2018, Int. J. Prod. Res..

[24]  Anjali Awasthi,et al.  A goal-oriented approach based on fuzzy axiomatic design for sustainable mobility project selection , 2019 .

[25]  Abolfazl Gharaei,et al.  Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation , 2019 .

[26]  Eduardo José Solteiro Pires,et al.  Grey wolf optimization for PID controller design with prescribed robustness margins , 2016, Soft Comput..

[27]  Anjali Awasthi,et al.  An integrated approach based on system dynamics and ANP for evaluating sustainable transportation policies , 2018, International Journal of Systems Science: Operations & Logistics.

[28]  Min-Yuan Cheng,et al.  Symbiotic Organisms Search: A new metaheuristic optimization algorithm , 2014 .

[29]  Seyed Ashkan Hoseini Shekarabi,et al.  Modelling And optimal lot-sizing of the replenishments in constrained, multi-product and bi-objective EPQ models with defective products: Generalised Cross Decomposition , 2020, International Journal of Systems Science: Operations & Logistics.

[30]  S. M. Mousavi,et al.  Sustainable supplier selection by a new decision model based on interval-valued fuzzy sets and possibilistic statistical reference point systems under uncertainty , 2019 .

[31]  Ching-Chih Tsai,et al.  Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation , 2011, IEEE Transactions on Industrial Electronics.

[32]  Masoud Rabbani,et al.  A hybrid robust possibilistic approach for a sustainable supply chain location-allocation network design , 2018, International Journal of Systems Science: Operations & Logistics.

[33]  Yan Wang,et al.  Convergence analysis and performance of an improved gravitational search algorithm , 2014, Appl. Soft Comput..

[34]  Haibin Duan,et al.  An improved constrained differential evolution algorithm for unmanned aerial vehicle global route planning , 2015, Appl. Soft Comput..

[35]  P. Helo,et al.  Virtual factory system design and implementation: integrated sustainable manufacturing , 2018 .

[36]  Jaehong Lee,et al.  A modified symbiotic organisms search (mSOS) algorithm for optimization of pin-jointed structures , 2017, Appl. Soft Comput..

[37]  Pascal Bouvry,et al.  Particle swarm optimization: Hybridization perspectives and experimental illustrations , 2011, Appl. Math. Comput..

[38]  Vikram Kumar Kamboj.  A novel hybrid PSO–GWO approach for unit commitment problem , 2015, Neural Computing and Applications.

[39]  Jun Wang,et al.  Sequential convex programming for nonlinear optimal control problems in UAV path planning , 2018 .

[40]  Hongxia Ji,et al.  Multi-UAVs tracking target in urban environment by model predictive control and Improved Grey Wolf Optimizer , 2016 .

[41]  Majdi M. Mafarja,et al.  Hybrid Whale Optimization Algorithm with simulated annealing for feature selection , 2017, Neurocomputing.

[42]  Abolfazl Gharaei,et al.  Joint Economic Lot-sizing in Multi-product Multi-level Integrated Supply Chains: Generalized Benders Decomposition , 2020, International Journal of Systems Science: Operations & Logistics.

[43]  Salwa Hanim Abdul-Rashid,et al.  Economic order quantity models for items with imperfect quality and emission considerations , 2018 .

[44]  Wei Liu,et al.  Bi-level programming based real-time path planning for unmanned aerial vehicles , 2013, Knowl. Based Syst..

[45]  Ran Dai,et al.  Two Approaches for Path Planning of Unmanned Aerial Vehicles with Avoidance Zones , 2017 .

[46]  Provas Kumar Roy,et al.  Grey wolf optimization applied to economic load dispatch problems , 2016 .

[47]  Y. Tsao,et al.  Design of a carbon-efficient supply-chain network under trade credits , 2015 .

[48]  Lhassane Idoumghar,et al.  Hybrid Differential Evolution Algorithm Employed for the Optimum Design of a High-Speed PMSM Used for EV Propulsion , 2017, IEEE Transactions on Industrial Electronics.

[49]  Nita H. Shah,et al.  Integrating credit and replenishment policies for deteriorating items under quadratic demand in a three echelon supply chain , 2018, International Journal of Systems Science: Operations & Logistics.

[50]  Francisco J. Rodríguez,et al.  Hybrid Metaheuristics Based on Evolutionary Algorithms and Simulated Annealing: Taxonomy, Comparison, and Synergy Test , 2012, IEEE Transactions on Evolutionary Computation.

[51]  Sreenatha G. Anavatti,et al.  State-of-the-Art Intelligent Flight Control Systems in Unmanned Aerial Vehicles , 2018, IEEE Transactions on Automation Science and Engineering.

[52]  Junjie Li,et al.  Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions , 2011, Inf. Sci..

[53]  Abolfazl Gharaei,et al.  An integrated multi-product, multi-buyer supply chain under penalty, green, and quality control polices and a vendor managed inventory with consignment stock agreement: The outer approximation with equality relaxation and augmented penalty algorithm , 2019, Applied Mathematical Modelling.