Intelligent Optimization Algorithms for Solving the Integrated Nesting and Tool Path Problem for CNC Sheet Cutting Machines

The paper considers the problem of developing intelligent algorithms for solving the integrated optimization problem of nesting and the tool routing for CNC sheet cutting machines, dubbed “The Integrated Nesting and Routing Problem (INRP)”. INRP combines two well-known optimization problems: the irregular strip packing problem (Nesting Problem), which belongs to the class of Cutting & Packing problem and the problem of optimal tool path routing for CNC sheet cutting machines (Tool Path Problem or Cutting Path Determination Problem). As an objective function, INRP uses an integrated additive cost criterion: the cost of the material used for nesting and the cutting process cost on CNC technological equipment. In this paper, INRP is considered in relation to the class of rectangular congruent parts, which are grouped with the possibility of using the common cut technique. In this case, the so-called multi-contour cutting technique is used. Two algorithms for the rectangular parts packing and tool routing are proposed, aimed at minimizing the cutting process cost and the total objective function. For the packing result with the minimum value of the integrated objective function, a control program for the CNC laser cutting machine is automatically generated. The results of computing experiments are presented. It is also shown that in order to generate a set of admissible nesting layouts at the first stage of solving the INRP problem, it is advisable to use neural networks.