In this paper, an improved initial random population strategy using a binary (0–1) representation of continuum structures is developed for evolving the topologies of path generating complaint mechanism. It helps the evolutionary optimization procedure to start with the structures which are free from impracticalities such as ‘checker-board’ pattern and disconnected ‘floating’ material. For generating an improved initial population, intermediate points are created randomly and the support, loading and output regions of a structure are connected through these intermediate points by straight lines. Thereafter, a material is assigned to those grids only where these straight lines pass. In the present study, single and two-objective optimization problems are solved using a local search based evolutionary optimization (NSGA-II) procedure. The single objective optimization problem is formulated by minimizing the weight of structure and a two-objective optimization problem deals with the simultaneous minimization of weight and input energy supplied to the structure. In both cases, an optimization problem is subjected to constraints limiting the allowed deviation at each precision point of a prescribed path so that the task of generating a user-defined path is accomplished and limiting the maximum stress to be within the allowable strength of material. Non-dominated solutions obtained after NSGA-II run are further improved by a local search procedure. Motivation behind the two-objective study is to find the trade-off optimal solutions so that diverse non-dominated topologies of complaint mechanism can be evolved in one run of optimization procedure. The obtained results of two-objective optimization study is compared with an usual study in which material in each grid is assigned at random for creating an initial population of continuum structures. Due to the use of improved initial population, the obtained non-dominated solutions outperform that of the usual study. Different shapes and nature of connectivity of the members of support, loading and output regions of the non-dominated solutions are evolved which will allow the designers to understand the topological changes which made the trade-off and will be helpful in choosing a particular solution for practice.

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