An agent-based heuristics optimisation model for production scheduling of make-to-stock connector plates manufacturing systems

被引:0
作者
Madi, Faris [1 ,2 ]
Al-Bazi, Ammar [3 ]
Buckley, Steve [1 ]
Smallbone, John [2 ]
Foster, Karl [2 ]
机构
[1] Coventry Univ, Fac Engn Environm & Comp, Coventry CV1 5FB, England
[2] Wolf Syst Ltd, Shilton Ind Estate, Coventry CV7 9QL, England
[3] Aston Univ, Coll Business & Social Sci, Aston Business Sch, Birmingham B4 7ET, England
关键词
Multi agent-based model; Heuristics optimisation; Production scheduling; Make-to-Stock environment; Demand and operational constraints; INVENTORY; CAPACITY; ORDER; CONSTRAINTS; DEMAND; INVESTMENT; ALLOCATION;
D O I
10.1007/s00500-023-09506-w
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The manufacturing systems' success directly relates to their accurate, reliable and flexible schedules, including how production is planned and scheduled and which constraints are considered in generating the schedules. The study's objective arises from the need to generate an optimal production scheduling system in a connecting plates manufacturing company that works on a Make-To-Stock basis. This research investigates the impact of demand and operational constraints on production schedules, including the facility capacity, operators and machines availability, raw materials availability, inventory level and warehouse capacity. A multi-agent-based optimisation model is developed to face the complexity of considering demand and operational constraints and reflects their impact on generating a reliable production schedule. This model involves a proposed heuristic algorithm that considers demand and operations constraints in such a manufacturing environment and optimises the production schedule based on these restrictions/requirements. A real-life case study based on a connecting plates manufacturer company is used as a test bench of the proposed agent-based heuristic optimisation model. The proposed algorithm is compared with other related approaches to check its superiority based on key criteria, including inventory levels, missed/unsatisfied orders and total production time. Results show that the proposed heuristics algorithm reduced the number of missed orders by 34% compared with similar approaches.
引用
收藏
页码:5899 / 5919
页数:21
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