• Ayani Nandi
• Dr Vikram Kumar

Recently developed Harris hawks optimizer has natural performance for discovery the optimum solution in global search space region without getting trapped into earlier convergence though the exploitation stage of the current Harris hawks optimization algorithm is underprivileged. In this research paper hybrid form of Harris hawks optimization algorithm mutual with canis lupus which is basically grey wolf optimization algorithm has established to find the different types of solution of optimization problem, non-convex, nonlinear and multidisciplinary engineering design problem. In this proposed research paper the exploitation stage of the present algorithm HHO has been further improved using grey wolf optimizer to expand its local and global search capability. The effectiveness of the proposed optimizer has been tested for various engineering design and optimization problems and it has been found that the proposed algorithm yields better results for multi-disciplinary design and optimization problems, as compared to others heuristics and meta-heuristics search algorithms.

Harris Hawks Optimization, Meta-Heuristics Search Algorithm, Multidisciplinary Engineering Design Problem.

"E-HHO: An Enhanced Harris Hawks Optimizer with improved Local Search Capability for Multi-Disciplinary Engineering Design and Optimization Problems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.1583-1607, March-2019, Available :http://www.jetir.org/papers/JETIREL06240.pdf

"E-HHO: An Enhanced Harris Hawks Optimizer with improved Local Search Capability for Multi-Disciplinary Engineering Design and Optimization Problems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp1583-1607, March-2019, Available at : http://www.jetir.org/papers/JETIREL06240.pdf