Mixed-model lines are used to produce several kinds of models in small lots without carrying large inventories. The production sequence for the mixed-model sequencing problem depends on the goals of the production facility. In order to enjoy the useful application of these lines, it is vital to devise a schedule for assembling the different products to be determined. Based on the NP-hardness of the problem, this present paper introduces an imperialist competitive algorithm (ICA) in three phases so as to solve a just-in-time (JIT) sequencing problem where the diversity of production rates to be optimized. Performance of the ICA was compared against two other search heuristics genetic algorithm (GA) and simulated annealing (SA) in small, medium and large problems. To compare presented algorithm with previous ones, an extensive computational study on 3 sets of benchmark problems has been conducted. Experimental results showed that our algorithm outperforms the previous algorithms, in respect of comparison metric.
Key words: Mixed-model sequencing, just-in-time, imperialist competitive algorithm, genetic algorithm, simulated annealing.
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