Title :
Mixed packing strategy for mass-product distributions and its Minimum Unpacking Problem
Author_Institution :
Inst. of Syst. Eng., Northeastern Univ., Shenyang, China
fDate :
May 31 2014-June 2 2014
Abstract :
Packing and unpacking are necessary operations in the product distribution processes of mass manufacturing. To reduce unpacking operation numbers, some Chinese enterprises designed an innovative packing strategy. It is refereed as “Multi-Type Mixed Packing with Variable Ratio”. The new packing strategy generates a new optimization problem named as “Minimum Unpacking Problem”. We propose the mathematical model and solution approach of minimum unpacking problem. By using the model and solution approach, the performances of three kinds of packing strategies which are the suggested mixed packing strategy, and single-type packing strategy and fixed ratio mixed packing strategy, are compared by simulation for a lot of different situations including different sizes, different supply-demand rate, and different distributions of demands. The applicable cases for each packing strategies are pointed. The simulation results have shown us that the suggested variable mixed packing strategy can greatly reduce the unpacking operation numbers in the distribution processes of mass-made products by using minimum unpacking optimization. It can bring considerable profits to the enterprises.
Keywords :
bin packing; goods distribution; mass production; optimisation; Chinese enterprises; fixed ratio mixed packing strategy; mass manufacturing; mass-product distribution processes; mathematical model; minimum unpacking optimization problem; multitype mixed packing with variable ratio; single-type packing strategy; solution approach; supply-demand rate; variable mixed packing strategy; Correlation; Linear programming; Manufacturing; Mathematical model; Optimization; Radiofrequency identification; Reactive power; Packing and unpacking; RFID; distribution network; mass manufacturing; minimum unpacking problem; optimization;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852601