A new optimization method namely the Search and Rescue optimization algorithm (SAR) is presented here to solve constrained engineering optimization problems. This metaheuristic algorithm imitates the explorations behavior of humans during search and rescue operations. The ε-constrained method is utilized as a constraint-handling technique. Besides, a restart strategy is proposed to avoid local infeasible minima in some complex constrained optimization problems. SAR is applied to solve 18 benchmark constraint functions presented in CEC 2010, 13 benchmark constraint functions, and 7 constrained engineering design problems reported in the specialized literature. The performance of SAR is compared with some state-of-the-art optimization algorithms. According to the statistical comparison results, the performance of SAR is better or highly competitive against the compared algorithms on most of the studied problems.

本文提出了一种新的优化方法，即搜索和救援优化算法（SAR），以解决受约束的工程优化问题。这种元启发式算法模仿了搜索和救援行动中人类的探索行为。ε约束方法被用作约束处理技术。此外，提出了一种重启策略，以避免在某些复杂的约束优化问题中出现局部不可行的最小值。SAR用于解决CEC 2010中提出的18个基准约束函数，13个基准约束函数和专业文献中报告的7个约束工程设计问题。将SAR的性能与一些最新的优化算法进行了比较。根据统计比较结果，