Scheduling multiple servers to facilitate just-in-time part-supply in automobile assembly lines

被引:13
|
作者
Peng, Tao [1 ]
Zhou, Binghai [1 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Assembly line; Ant colony optimization; Multiple server scheduling problem; Part-supply; Tree search; ANT COLONY OPTIMIZATION; PARALLEL MACHINES; FEEDING POLICIES; TOTAL TARDINESS; MODEL; ALGORITHM; HEURISTICS; JOBS; CLASSIFICATION; SUPERMARKET;
D O I
10.1108/AA-08-2017-102
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose With regard to product variety and cost competition, just-in-time (JIT) part-supply has become a critical issue in automobile assembly lines (AALs). This paper aims to investigate a multiple server scheduling problem (MSSP) encountered in the JIT part-supply process of AALs. Parts are stored in boxes and allotted from the JIT-supermarket to consumptive stations with a multiple server system. The schedule is to dispatch and sequence material boxes on each server for minimizing line-side inventory levels. Design/methodology/approach A mixed integer linear programming (MILP) model is established to formulate the proposed MSSP to pave the way for CPLEX procedure. Considering the high complexity of MSSP, a hybrid ant colony optimization (HACO) approach is developed by integrating basic ant colony optimization (ACO) with local optimizers that comprise of a fast local search and a tailored breadth-first tree search method. Findings Both CPLEX and HACO approach are capable of solving small-scale instances to optimality within reasonable computation time. The proposed HACO has been well enhanced with the embedded fast local search and tailored breadth-first tree search, and it performs robustly in a statistically significant manner when applied to real-world scale instances. Originality/value No stock-outs constraints and weighted line-side inventory level are considered in this paper, and the MSSP is solved satisfactorily to facilitate an efficient JIT part-supply of the AAL. In terms of the algorithm design, a tree search-based local optimizer is embedded into ACO to combine the mechanisms of ACO and problem-specific optimization.
引用
收藏
页码:347 / 360
页数:14
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