2019•RAIRO - Operations ResearchRequires access

The production planning problem of orders in small foundries

Maria Gabriela Stevanato Furtado, Victor Claudio Bento Camargo, Franklina M. B. Toledo

Open publisher page 6 citations

Abstract

The production planning problem in market-driven foundries consists of determining the alloys to be melted and the items to be produced. A production plan is defined based on the foundry book order that compiles customer requests. Each customer order can be composed of items of different types and made from different alloys. In the literature, production planning does not usually consider the customers’ orders, i.e., items are independently handled. However, in practical situations, several orders cannot be partially delivered. An order can be delivered only when all of its items have been produced, which often results in delays in meeting the customer demands. Conversely, some orders may be split, which would incur delivering costs. This paper addresses the production planning problem of orders in market-driven foundries, which is considered a gap in the literature. A mathematical model and a relax-and-fix heuristic are proposed to address the problem. An experimental evaluation using synthetic datasets and a real dataset compares the proposed methods with the practical policy planning and a state-of-the-art method that solve the production planning problem of items. The results demonstrate the relevance of the production planning of orders.

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The production planning problem in market-driven foundries consists of determining the alloys to be melted and the items to be produced. A production plan is defined based on the foundry book order that compiles customer requests. Each customer order can be composed of items of different types and made from different alloys. In the literature, production planning does not usually consider the customers’ orders, i.e., items are independently handled. However, in practical situations, several orders cannot be partially delivered. An order can be delivered only when all of its items have been produced, which often results in delays in meeting the customer demands. Conversely, some orders may be split, which would incur delivering costs. This paper addresses the production planning problem of orders in market-driven foundries, which is considered a gap in the literature. A mathematical model and a relax-and-fix heuristic are proposed to address the problem. An experimental evaluation using synthetic datasets and a real dataset compares the proposed methods with the practical policy planning and a state-of-the-art method that solve the production planning problem of items. The results demonstrate the relevance of the production planning of orders.

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Available abstract

The production planning problem in market-driven foundries consists of determining the alloys to be melted and the items to be produced. A production plan is defined based on the foundry book order that compiles customer requests. Each customer order can be composed of items of different types and made from different alloys. In the literature, production planning does not usually consider the customers’ orders, i.e., items are independently handled. However, in practical situations, several orders cannot be partially delivered. An order can be delivered only when all of its items have been produced, which often results in delays in meeting the customer demands. Conversely, some orders may be split, which would incur delivering costs. This paper addresses the production planning problem of orders in market-driven foundries, which is considered a gap in the literature. A mathematical model and a relax-and-fix heuristic are proposed to address the problem. An experimental evaluation using synthetic datasets and a real dataset compares the proposed methods with the practical policy planning and a state-of-the-art method that solve the production planning problem of items. The results demonstrate the relevance of the production planning of orders.

Key concepts: Production planning, Production (economics), Order (exchange), Plan (archaeology), Heuristic, Computer science, Relevance (law), Operations research

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