Cutting Unequal Rectangular Boards from Cylindrical Logs in Wood Products Manufacturing: A Heuristic Approach

In recent years, the global wood products market has become highly competitive. Due to this, sawmills seek to improve their efficiency throughout their production process. In this regard, improving sawing efficiency through improved cutting strategies is vital for preventing overproduction and waste issues. In this paper, we deal with the sawing optimization problem defined as the problem of cutting rectangular boards from cylindrical logs with circular cross sections. In particular, we consider a sawing pattern that is highly beneficial for wood manufacturing, namely cant sawing. We take into account feasibility, capacity, non-overlapping, and technical constraints of the sawing process. We first develop an exact model of this combinatorial optimization problem as a mixed-integer nonlinear programming (MINLP) problem. However, this exact model involves a high level of combinatorics and requires considerable computation time, becoming computationally intractable as the problem size increases. To deal with this challenge, we develop a constructive heuristic approach, namely strip-bottom-left-fill (SBLF) heuristic, that builds a feasible cutting according to a list of ordered rectangles and a set of placement policies. The simulation results confirm the superiority of our proposed approach over the MINLP model and a state-of-the-art heuristic approach in terms of computational effort as well as memory and search requirements while preserving cutting yield efficiency