For assembly lines of circuit printing board (PCBs), this study investigated an integrated scheduling problem of the component allocation problem (CAP) and component placement sequence problem (CPSP) with the fixed interval preventive maintenance to minimize the maximum completion time (${\mathrm{C}}_{\max }$), the total energy consumption (TEC), and the total maintenance time (TMT) simultaneously. An improved spider monkey optimization (ISMO) algorithm is proposed with selecting the local leader (LL) and the global leader (GL) using a parallel lattice coordinate system. We compared the proposed ISMO algorithm with the classical optimizations, including SMO, NSGA-Ⅲ, DE, and PSO, by the production data of an enterprise; the results showed that the ISMO algorithm can obtain pareto solutions with better convergence and diversity.

This paper investigates the hybrid flow shop scheduling problem with lot streaming, which integrates the order lot problem (OLP), order sequence problem (OSP), and lots assignment problem (LAP), with the objective of minimizing both the maximum completion time ($C_{max}$) and the total tardiness (TT) simultaneously. An improved spider monkey optimization (I-SMO) algorithm is proposed by combining the advantages of crossover and mutation operations of a genetic algorithm (GA) with the spider monkey optimization algorithm. The contribution value method is employed to select both global and local leaders. Experimental comparisons with classical optimization algorithms, including particle swarm optimization (PSO) and differential evolution (DE), were conducted to demonstrate the superiority of the proposed I-SMO algorithm.