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Li, T.
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Li, T.
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Li, T.
Zhang, J.
spellingShingle Lv, Z.
Li, T.
Zhang, J.
Cybernetics and Information Technologies
An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
General Computer Science
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spelling Lv, Z. Li, T. Zhang, J. 1314-4081 Walter de Gruyter GmbH General Computer Science http://dx.doi.org/10.1515/cait-2015-0075 <jats:title>Abstract</jats:title> <jats:p>In the MTO (Make-To-Order) and MTS (Make-To-Stock) mixed production environment, it is important to make an accurate delivery promise on the ordering stage because the customer’s demand with unmatched production capacity is not always satisfied. A quick order promising method for an iron and steel enterprise, based on short-term production capacity balancing planning is proposed in this paper. With the help of this method, ATP (Available-To-Promise) concept is extended to RATP (Resource-Available-To-Promise) and DTP (Delivery-To-Promise) is given while making the resource promise. A heuristic method is developed to match the available resources with the order demand and the actual data testing results have shown that the method proposed can meet the demand of online order promising in a relatively short time.</jats:p> An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning Cybernetics and Information Technologies
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title An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_unstemmed An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_full An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_fullStr An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_full_unstemmed An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_short An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_sort an heuristic order promising method based on short-term production capacity balancing planning
topic General Computer Science
url http://dx.doi.org/10.1515/cait-2015-0075
publishDate 2015
physical 147-158
description <jats:title>Abstract</jats:title> <jats:p>In the MTO (Make-To-Order) and MTS (Make-To-Stock) mixed production environment, it is important to make an accurate delivery promise on the ordering stage because the customer’s demand with unmatched production capacity is not always satisfied. A quick order promising method for an iron and steel enterprise, based on short-term production capacity balancing planning is proposed in this paper. With the help of this method, ATP (Available-To-Promise) concept is extended to RATP (Resource-Available-To-Promise) and DTP (Delivery-To-Promise) is given while making the resource promise. A heuristic method is developed to match the available resources with the order demand and the actual data testing results have shown that the method proposed can meet the demand of online order promising in a relatively short time.</jats:p>
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author Lv, Z., Li, T., Zhang, J.
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description <jats:title>Abstract</jats:title> <jats:p>In the MTO (Make-To-Order) and MTS (Make-To-Stock) mixed production environment, it is important to make an accurate delivery promise on the ordering stage because the customer’s demand with unmatched production capacity is not always satisfied. A quick order promising method for an iron and steel enterprise, based on short-term production capacity balancing planning is proposed in this paper. With the help of this method, ATP (Available-To-Promise) concept is extended to RATP (Resource-Available-To-Promise) and DTP (Delivery-To-Promise) is given while making the resource promise. A heuristic method is developed to match the available resources with the order demand and the actual data testing results have shown that the method proposed can meet the demand of online order promising in a relatively short time.</jats:p>
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spelling Lv, Z. Li, T. Zhang, J. 1314-4081 Walter de Gruyter GmbH General Computer Science http://dx.doi.org/10.1515/cait-2015-0075 <jats:title>Abstract</jats:title> <jats:p>In the MTO (Make-To-Order) and MTS (Make-To-Stock) mixed production environment, it is important to make an accurate delivery promise on the ordering stage because the customer’s demand with unmatched production capacity is not always satisfied. A quick order promising method for an iron and steel enterprise, based on short-term production capacity balancing planning is proposed in this paper. With the help of this method, ATP (Available-To-Promise) concept is extended to RATP (Resource-Available-To-Promise) and DTP (Delivery-To-Promise) is given while making the resource promise. A heuristic method is developed to match the available resources with the order demand and the actual data testing results have shown that the method proposed can meet the demand of online order promising in a relatively short time.</jats:p> An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning Cybernetics and Information Technologies
spellingShingle Lv, Z., Li, T., Zhang, J., Cybernetics and Information Technologies, An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning, General Computer Science
title An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_full An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_fullStr An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_full_unstemmed An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_short An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
title_sort an heuristic order promising method based on short-term production capacity balancing planning
title_unstemmed An Heuristic Order Promising Method Based on Short-Term Production Capacity Balancing Planning
topic General Computer Science
url http://dx.doi.org/10.1515/cait-2015-0075