A new cutting-stock heuristic for scheduling production

doi:10.1016/0305-0548(86)90027-4

Computers & Operations Research

Volume 13, Issue 4, 1986, Pages 403-410

https://doi.org/10.1016/0305-0548(86)90027-4 Get rights and content

Abstract

This study interprets a scheduling problem in the woven fiberglass industry as an example of the cutting-stock problem; where wasted production capacity rather than wasted material is to be controlled. The solution is complicated due to the need to consider setup costs, so a heuristic is developed and tested. Comparison to one company's a historical production decisions indicates that both wasted capacity and setup Costs can be substantially reduced through application of the heuristic.

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There are more references available in the full text version of this article.

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Heuristic methods for gang-rip saw arbor design
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We consider the problem of design and scheduling of arbors for a computer assisted gang-rip saw system. Such systems are typically used within the furniture manufacturing industry for processing lumber. We discuss the computational complexity of the problem, and develop several heuristic procedures for solving it. These procedures are based on the principles of local improvement, simulated annealing, and genetic algorithms. The results of a computational experiment are also presented.
Nesting planning based on production priorities and technological efficiency
1995, European Journal of Operational Research
The purpose and contribution of this work is in developing a methodology for integrating nesting technology with production priorities. Production priorities are based on a due-date (e.g., from an MRP-II program) and other management factors. A good nesting plan requires high raw material utilization. Economic operation demands low set-up frequency between nesting plans. These three factors usually conflict. We present here a parametric multi-objective mathematical programming formulation that takes account of these factors and their tradeoffs, and suggests an optimal solution to the problem.
An interactive technique for the cutting stock problem with multiple objectives
1994, European Journal of Operational Research
This paper deals with the two-dimensional cutting stock problem in which a specified number of different rectangular pieces are required to be cut from a stock of sheets of finite dimensions in such a way that several objectives will be satisfied simultaneously. It is shown how this problem can be expressed as a large scale multiple-objective integer linear programming and solved by applying an interactive technique known from multiple criteria decision making. Furthermore, a new cutting procedure is proposed, based on homogeneous strips, to generate cutting patterns with minimum waste. The effectiveness of the interactive technique as well as the cutting procedure is illustrated, in detail, by a numerical example. All the given approaches are implemented on a microcomputer and experimented using a real data from automotive company. Sample of the input/output computer screens and the suggestions for future work are also reported.
Knowledge based approach to the cutting stock problem
1992, Mathematical and Computer Modelling
Stock Cutting Problem (CSP) is an instance of a particularly difficult combinatorial optimization problem where a few geometrical patterns must be selected and arranged so as to minimize the total cost of the underlying process. A survey of the literature on CSP reveals that the scope of this famous problem applications has expanded in the recent thirty-five years from pallet loading, packing, and industrial production planning to computer operations to telecommunications. Three major trends of engineering activities are identified and discussed in detail: integration of applications, shift from optimization to control, and construction of new related problems.
On the other hand, the notorious difficulties of the popular Linear Programming approach to solving CSP (e.g., handling non-linear constraints and integer solutions) have been only partially remedied by a host of heuristic search schemes. We propose a learning expert system CUT addressing the above difficulties. CUT achieves efficient cutting pattern knowledge acquisition and inference by combining Simulated Annealing and Case Based Reasoning. CUT is implemented in PROLOG. Logic Programming implementation offers the advantages of natural symbolic data processing, declarative programming, and automatic search.
Heuristic methods and applications: A categorized survey
1989, European Journal of Operational Research
An extensive search of journal publications on heuristic methods and applications produced 442 articles published in 37 journals during the last sixteen years. A scheme is employed to categorize each article according to 12 classes of heuristic approaches and 144 areas of applications (the latter taken from the OR/MS subject classification codes). An analysis of these data reveals some interesting historical patterns and directions for future work. This categorized survey should be helpful to students, teachers, researchers and practitioners interested in heuristics.
Optimizing an aluminum extrusion process
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^∗: Robert T. Sumichrast received his B.S. in Physics from Purdue University in 1979. He developed inventory control and scheduling systems for Owens Corning Fiberglass Corporation during 1982 and 1983. In 1984 he received his Ph.D. in Management Science from Clemson University. He is currently the Assistant Professor of Management Science at Virginia Polytechnic Institute and State University. His primary area of research is Scheduling and Inventory Control.

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A new cutting-stock heuristic for scheduling production

Abstract

A heuristic programming solution to a nonlinear cutting-stock problem

Mgmt Sci.

The trim problem

Mgmt Sci.

A linear programming approach to the cutting-stock problem

Opns Res.

A linear programming approach to the cutting-stock problem—Part II

Opns Res.