Bixi Zhang

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The flow shop scheduling problem (FSSP) is a NP-HARD combinatorial problem with strong industrial background. Among the meta-heuristics, genetic algorithms attracted a lot of attention. However, lacking the major evolution direction, the effectiveness of regular genetic algorithm is restricted. In this paper, the particle swarm optimization algorithm (PSO)(More)
With the development of information technology, retail companies have accumulated a huge amount of data which may be potentially valuable but currently untapped. In a changing competitive environment, the usage of data mining to tap the potential knowledge and its decision-supporting applications has a crucial implication for retailer in competitiveness(More)
The paper simulates worker-station assignment based on learning- forgetting, and develops the model of the maximum learning incremental. The goal of this model is the maximum learning incremental. Job rotation is used in this model. One worker is trained more than one job. It makes the process of learning longer. After the long process of learning, workers(More)
In Make-to-Order and Manual Operation System(MTO/MOS), product quality closely relats to worker skills, work attitude, work status, incentive and punishment mechanisms. While facing to disturbances of emergency orders insertion, equipment failure, loss of workers, the quality of the product are neglectly affected and the qualified rate changes Severely. In(More)
This paper considers a two-machine flow shop scheduling problem with deteriorating jobs in which the processing times of jobs are dependent on their starting times in the sequence. The objective is to minimize the weighted sum of makespan and total completion time. To analyse the problem, we propose a mixed integer programming model, and discuss several(More)
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