As the status of order picking in the warehousing and distribution system has been raised,the work-rest scheduling of picking becomes particularly important.Although science and technology have developed rapidly,manua...As the status of order picking in the warehousing and distribution system has been raised,the work-rest scheduling of picking becomes particularly important.Although science and technology have developed rapidly,manual picking is still essential and indispensable.However,previous researches focused on the study of the sequencing,ignoring human factors.The paper presents a work-rest schedule model in parts to picker picking system.Two objectives are proposed that include minimizing the picking time and minimizing picking error rate.And workers'fatigue,workload is taken into account in the manual order picking systems because the fatigue can have a large influence on the picking time and the picking error rate.A genetic algorithm is used to solve a multi-objective optimization problem that the model concerns and looking for a Pareto front as the most effective methods for solving this problem.Once the original data is given,the work-rest scheduling model is built and the work sequence,and the number of breaks are determined to be chosen by decision makers.In addition,a case study of the model is used to confirm that the model is effective and it is necessary to consider the human factor in the picking system.展开更多
文摘As the status of order picking in the warehousing and distribution system has been raised,the work-rest scheduling of picking becomes particularly important.Although science and technology have developed rapidly,manual picking is still essential and indispensable.However,previous researches focused on the study of the sequencing,ignoring human factors.The paper presents a work-rest schedule model in parts to picker picking system.Two objectives are proposed that include minimizing the picking time and minimizing picking error rate.And workers'fatigue,workload is taken into account in the manual order picking systems because the fatigue can have a large influence on the picking time and the picking error rate.A genetic algorithm is used to solve a multi-objective optimization problem that the model concerns and looking for a Pareto front as the most effective methods for solving this problem.Once the original data is given,the work-rest scheduling model is built and the work sequence,and the number of breaks are determined to be chosen by decision makers.In addition,a case study of the model is used to confirm that the model is effective and it is necessary to consider the human factor in the picking system.
