Improved ant colony algorithm for the mixed-model parallel two-sided assembly lines balancing problem.

In response to the increasing demand for individualized products in the 'small-lot, multi-variety' market, there is an urgent need to enhance the efficiency and intelligence level of assembly lines. To address this, a novel solution method for the mixed-model parallel two-sided assembly lines balancing problem (MMPTSALBP) is proposed. The first step is to define the type and layout of the parallel two-sided assembly lines. Next, a mathematical model is constructed with the objective of minimizing the number of workstations required for the MMPTSALBP, proposing an improved ant colony algorithm that utilizes double string representation for the initial solution encoding method and a double pheromone matrix update to solve the model. Its efficiency is tested on benchmark datasets according to some performance measures and classifications. A study validates its effectiveness on 25 classical arithmetic cases by comparison with the solutions of an heuristic algorithm and an artificial fish swarm algorithm that had been reported to perform well. [ABSTRACT FROM AUTHOR]