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Showing posts with label problem. Show all posts
Showing posts with label problem. Show all posts

An iterative sequential heuristic procedure to a real-life 1.5-dimensional cutting stock problem [An article from: European Journal of Operational Research]

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An iterative sequential heuristic procedure to a real-life 1.5-dimensional cutting stock problem [An article from: European Journal of Operational Research] Overviews

This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
This paper addresses a real-life 1.5D cutting stock problem, which arises in a make-to-order plastic company. The problem is to choose a subset from the set of stock rectangles to be used for cutting into a number of smaller rectangular pieces so as to minimize total production cost and meet orders. The total production cost includes not only material wastage, as in traditional cutting stock problems, but also production time. A variety of factors are taken into account, like cutter knife changes, machine restrictions, due dates and other work in progress limitations. These restrictions make the combinatorial structure of the problem more complex. As a result, existing algorithms and mathematical models are no longer appropriate. Thus we developed a new 1.5D cutting stock model with multiple objectives and multi-constraints and solve this problem in an incomplete enumerative way. The computational results show that the solution procedure is easy to implement and works very well.


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Solving the biobjective zero-one knapsack problem by an efficient LP-based heuristic [An article from: European Journal of Operational Research]

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Solving the biobjective zero-one knapsack problem by an efficient LP-based heuristic [An article from: European Journal of Operational Research] Overviews

This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
In this paper, we propose a simple and useful method, the core of which is an efficient LP-based heuristic, for solving biobjective 0-1 knapsack problems. Extensive computational experiments show that the proposed method is able to generate a good approximation to the nondominated set very efficiently. We also suggest three qualitative criteria to evaluate such an approximation. In addition, the method can be extended to other problems having properties similar to the knapsack problem.


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