Manual Order Picking Route Optimization in Distribution Warehouse of Chain Furniture Retail Enterprise

Due to the effects of the COVID-19 pandemic and the rise of online shopping, the offline sales of IKEA Fuzhou have been declining since 2020. Because the cost of distribution warehouse is a major expense for offline chain furniture retailers, and the picking process is a key activity in distribution warehouse operations. To reduce the cost of distribution warehouse and alleviate the survival pressure of the offline chain furniture retailers, this paper focuses on optimizing the picking route of the IKEA Fuzhou distribution warehouse. It starts by creating a two-dimensional coordinate system for the storage location of the distribution warehouse using the traditional S-type picking strategy to calculate the distance and time of the sorting route. Then, the problem of optimizing the picking route is then transformed into the travelling salesman problem (TSP), and picking route optimization model is developed using a genetic algorithm to analyze the sorting efficiency and picking route optimization. Results show that the order-picking route using the genetic algorithm strategy is significantly better than the traditional S-type picking strategy, which can improve overall sorting efficiency and operations, reduce costs, and increase efficiency. Thus, this establishes an implementation process for the order-picking path based on genetic algorithm optimization to improve overall sorting efficiency and operations, reduce costs, increase efficiency, and alleviate the survival pressure of pandemic-affected enterprises.

Optimization of endwall contouring in axial compressor S-shaped ducts

This paper presents a numerical investigation of the potential aerodynamic benefits of using endwall contouring in a fairly aggressive duct with six struts based on the platform for endwall design optimization.The platform is constructed by integrating adaptive genetic algorithm（AGA）, design of experiments（DOE）, response surface methodology（RSM） based on the artificial neural network（ANN）, and a 3D Navier–Stokes solver.The visual analysis method based on DOE is used to define the design space and analyze the impact of the design parameters on the target function（response）.Optimization of the axisymmetric and the non-axisymmetric endwall contouring in an S-shaped duct is performed and evaluated to minimize the total pressure loss.The optimal ducts are found to reduce the hub corner separation and suppress the migration of the low momentum fluid.The non-axisymmetric endwall contouring is shown to remove the separation completely and reduce the net duct loss by 32.7%.