Express Delivery Handling Model Based on Monte Carlo Simulation and Linear Programming in the Background of Cloud Computing

Abstract

This paper addresses the purchase options for courier companies looking for the type and number of machines to handle couriers, using Monte Carlo simulation and linear programming to simulate the processing of courier companies. The Jacques-Bella test for normality is first used, and the original hypothesis that both the machine processing capacity and the number of couriers given retain the random variables obey a normal distribution. The data are integrated into hourly time units using the principle of additivity of the normal distribution. Problem 1 requires the optimal number of equipment 1 to meet the basic operation demand of the courier company. According to the daily conditions, the article sets linear programming constraints, using Monte Carlo simulation of the number of machines working per hour for 200 cycles and gets the result that 16 machines are required. Problem 2 requires a comparison of the costs of purchasing equipment 2 and equipment 1. Due to the limitations of the work cycle of equipment 2, the article simulates 50 Google cycles to obtain the result that purchasing of three equipment 2 would meet the requirements. Because equipment 1 program costs less, the courier company should choose to buy 4 equipment 1.