Chemical Reaction Optimization (CRO) is an

\r\noptimization metaheuristic inspired by the nature of chemical

\r\nreactions as a natural process of transforming the substances from

\r\nunstable to stable states. Starting with some unstable molecules with

\r\nexcessive energy, a sequence of interactions takes the set to a state of

\r\nminimum energy. Researchers reported successful application of the

\r\nalgorithm in solving some engineering problems, like the quadratic

\r\nassignment problem, with superior performance when compared with

\r\nother optimization algorithms. We adapted this optimization

\r\nalgorithm to the Printed Circuit Board Drilling Problem (PCBDP)

\r\ntowards reducing the drilling time and hence improving the PCB

\r\nmanufacturing throughput. Although the PCBDP can be viewed as

\r\ninstance of the popular Traveling Salesman Problem (TSP), it has

\r\nsome characteristics that would require special attention to the

\r\ntransactions that explore the solution landscape. Experimental test

\r\nresults using the standard CROToolBox are not promising for

\r\npractically sized problems, while it could find optimal solutions for

\r\nartificial problems and small benchmarks as a proof of concept.<\/p>\r\n","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 97, 2015"}