A Novel Ant Colony Optimization Algorithm for U-Shaped Line Balancing Problem

Abstract

The utilization of U-shaped layouts in place of the traditional straight-line configuration has become increasingly popular, with reported benefits of substantial improvements in productivity and quality. In this paper, a new design of ant colony optimization (ACO) is proposed for solving type 1 of the U-shaped line balancing problem (ULBP-1). The proposed algorithm made use of the trail information which is deposited between the task and the task selected position, and pheromone summation rules was adopted. The heuristic information is set to the position weight for tasks of ULBP-1, which synthesis consider processing time of the task and the number of successors/predecessors. The results of the computational experiments indicate that the proposed ACO-based algorithm performs quite effectively.