Warehouse assembly integrated product distribution route and technician scheduling optimization method
A technology of technicians and optimization methods, applied in the direction of instruments, data processing applications, forecasting, etc., can solve the problems affecting the efficiency of product distribution, incompleteness, not considering the time window, building team outsourcing options, lunch break requirements, etc., to improve quality. , Process optimization, improve the effect of optimization quality
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Embodiment 1
[0065] This embodiment proposes an optimization method for the distribution route of integrated products in the warehouse and assembly and the scheduling of technicians, such as figure 1 As shown, the optimization method includes the following steps:
[0066] Step S1, establishing a mixed integer programming model, the goal of which is to minimize operating costs under soft time windows, skill requirements, lunch break requirements, and outsourcing selection constraints. The operating costs include travel costs, penalty costs, and outsourcing costs.
[0067] For a given service time range (usually one day), for a batch of tasks (customer requests), a team of technicians with specific skills is required to complete each task, and each task requires the skill level of the relevant service personnel to reach a certain level. We consider that there are multiple equipment delivery and maintenance service providers, and their respective locations correspond to warehouse locations, a...
Embodiment 2
[0169] In this embodiment, the optimization method proposed in the above-mentioned embodiment 1 is tested. By collecting actual experimental data, the algorithm program is developed using Matlab R2014a, and runs on a computer with 1.8GHz Intel Core 4CPU and 8GB memory. The effectiveness of the optimization method proposed in the above-mentioned embodiment 1 is verified by comparing the method proposed in the above-mentioned embodiment 1 with the empirical decision-making method actually applied by the enterprise.
[0170] 1. Empirical decision-making methods for practical application in enterprises
[0171] The current practice of X logistics company under Company A is to artificially divide orders into m categories according to the location and approximate distribution of each order, where m represents the number of vehicles available for arrangement. For each category, find workers who can meet the skill level requirements for completing all orders in that category, generall...
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