A selective mutation based evolutionary programming for solving Cutting Stock Problem without contiguity

The cutting stock problem (CSP) is a combinatorial optimisation problem that involves cutting large stock sheets into smaller pieces. It has attracted vast attention along the years due to its applicability in many industries ranging from steel, glass, wood, plastic to paper manufacturing. A good solution to CSP is thus important as a mean to increase efficiency in these industrial sectors. In this paper, we present a selective mutation based evolutionary programming (SMBEP) for solving CSP without contiguity. We conduct experiments with our novel SMBEP on the benchmark problems of CSP. We show that the performance of our approach is slightly better than the previous results.