The template design problem is a constrained optimization problem originated from the printing industry. It involves printing several variations of a design onto one or more stencil sheets, where the aims are to minimize the number of stencils as well as the overproduction of prints of a particular design. Over the years, exact solution methods have been used to solve the problem. These methods could be useful for small to moderate-sized problem instances. However, when the problem instances are huge, the search space may easily grow too large for the systematic approaches. To date, no meta-heuristic or soft computing techniques have been used for this problem. In this paper, we propose the use of Extremal Optimization (EO) with multiple search operators for solving the template design problem. Different combinations of the search operators are tested via extensive numerical experiments. The results show that EO is indeed a feasible approach for template design optimization. The hybridization of EO with a deterministic local search has proven to be particularly effective.
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