Archives > Volume 13 | Number 2 | June 2018 > pp 169–178
Advances in Production Engineering & Management
Volume 13 | Number 2 | June 2018 | pp 169–178
A robust hybrid heuristic algorithm to solve multi-plant milk-run pickup problem with uncertain demand in automobile parts industry
Wu, Q.; Wang, X.; He, Y.D.; Xuan, J.; He, W.D.
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A B S T R A C T
Considering the actual situation of China's automobile industry, this paper pioneers the discussion of the multi-factory milk run pickup problem with uncertain demand and frequency (MFMRPP-UDF). Considering the balance between inventory cost and distribution cost, a mixed-integer programming model was built for the problem, and converted into a robust optimization model by the Chernoff-Hoeffding theorem; then, the adaptive genetic algo-rithm (AGA) and local search (LS) were combined into a general hybrid heu-ristic algorithm (AGA-LS) to solve the problem. Then, the proposed algorithm was run 10 times and contrasted with the standard GA. The results show that the AGA-LS outperformed the standard GA in the reduction of the overall cost. This research provides important insights into the cost efficiency of inventory and delivery in the automobile parts industry.
A R T I C L E I N F O
Keywords • Milk-run pickup problem, Optimization, Uncertain demand, Hybrid heuristic algorithm, Adaptive genetic algorithm, Local search
Corresponding author • Wang, X.
Article history • Received 21 February 2018, Revised 29 May 2018, Accepted 31 May 2018
Published on-line • 15 June 2018
E X P O R T C I T A T I O N
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