Solving the Laser Cutting Path Problem Using Population-Based Simulated Annealing with Adaptive Large Neighborhood Search

Abstract

This paper presents an alternative algorithm for solving the laser cutting path problem which was modeled as Generalized Traveling Salesman Problem (GTSP). The objective is to minimize the traveling distance of laser cutting of all profiles in a given layout, where a laser beam makes a single visit and then does the complete cut of individual profile in an optimum sequence. This study proposed a hybrid method combining population-based simulated annealing (SA) with an adaptive large neighborhood search (ALNS) algorithm to solve the cutting path problem. Recombination procedures were executed alternately using swap, reversion, insertion and removal-insertion through a fitness proportionate selection mechanism. In order to reduce the computing time and maintain the solution quality, the 35% proportion of population were executed in each iteration using the cultural algorithm selection method. The results revealed that the algorithm can solve several ranges of problem size with an acceptable percentage of error compared to the best known solution.

Evolutionary Algorithms for Optimization Sequence of Cut in the Laser Cutting Path Problem

“…Similarly, the empty path problems in laser cutting can be seen as an extension of the traveling salesman problem (TSP), a well-known NP-hard problem. Hajad et al [33] propose an approach for addressing the laser cutting path problem, formulated as a generalized traveling salesman problem (GTSP). Their study combines population-based simulated annealing (SA) with adaptive large neighborhood search (ALNS).…”

“…The study by Hajad et al [33] demonstrates a promising approach for tackling the laser cutting path problem, utilizing a combination of population-based simulated annealing and adaptive extensive neighborhood search techniques. Their method effectively solves problems of different scales and provides satisfactory accuracy compared to the bestknown solutions.…”

Improved Particle Swarm Optimization for Laser Cutting Path Planning

“…Several works investigated this issue. For example, Hajad et al [14] modeled the laser cutting path problem as a TSP and proposed a hybrid method combining population-based simulated annealing with an adaptive large neighborhood search algorithm to solve the problem. Rafał [15] introduced a focused ant colony algorithm to improve the performance through algorithm refinements and parallel implementation.…”