Discrete Size and Shape Optimization of Truss Structures Based on Job Search Inspired Strategy and Genetic Operations

Abstract

A meta-heuristic algorithm for discrete size and shape optimization of trusses via a job search inspired strategy together with genetic operators of mutation, selection, and crossover is proposed. The alternation of movements with respect to objective function and load bearing capacity of constructive decisions is provided. Being introduced is an intermediate search goal connected in terms of posed limitations with heightened suitability levels of individuals meeting the current requirements for the initial objective function. As soon as these conditions allow achieving a structure type which meets task limitations, requirements for the function value are redefined. This technique does not demand penalty functions that provide strict control of limitations in any algorithm usage, greater stability of the results received, and finding better solutions. The efficiency of this approach in terms of solution accuracy is demonstrated through five benchmark design examples, in comparison with other methods of discrete truss structure optimization.