Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10183
Title: Minimising earliness and tardiness by integrating production scheduling with shipping information
Authors: Ma, HL
Chan, FTS 
Chung, SH
Keywords: Production planning
Due date scheduling
Distribution
Genetic algorithm
Issue Date: 2013
Publisher: Taylor & Francis
Source: International journal of production research, 2013, v. 51, no. 8, p. 2253-2267 How to cite?
Journal: International journal of production research 
Abstract: Minimisation of earliness and tardiness is known to be critical to manufacturing companies because it may induce numerous tangible and intangible problems, i.e. extra storage cost, spacing, risk of damages, penalty, etc. In literature, earliness and tardiness is usually determined based on order due date, generally regarded as the time of delivering the finished products to the customers. In many papers, delivery time and cost required are usually simplified during the production scheduling. They usually assume that transportation is always available and unlimited. However, transportation usually constructs a critical portion of the total lead time and total cost in practice. Ignoring that will lead to an unreliable schedule. This is especially significant for electronic household appliances manufacturing companies as the studied company in this paper. In general, they usually rely on sea-freight transportation because of the economic reasons. As different sea-freight forwarders have different shipments to the same destination but with different shipping lead time, cost and available time. Adequately considering this shipping information with the production scheduling as an integrated model can minimise the costs induced by earliness and tardiness and the reliability of the schedule planned. In this paper, a two-level genetic algorithm (TLGA) is proposed, which is capable of simultaneously determining production schedule with shipping information. The optimisation reliability of the proposed TLGA is tested by comparing with a simple genetic algorithm. The results indicated that the proposed TLGA can obtain a better solution with lesser number of evolutions. In addition, a number of numerical experiments are carried out. The results demonstrate that the proposed integrated approach can reduce the tardiness, the storage cost, and shipping cost.
URI: http://hdl.handle.net/10397/10183
ISSN: 0020-7543
EISSN: 1366-588X
DOI: 10.1080/00207543.2012.718452
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