A genetic algorithm for 1,5 dimensional assortment problems with multiple objectives
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Roll assortment optimization in a paper mill: An integer programming approach
Computers and Operations Research
Solving a combined cutting-stock and lot-sizing problem with a column generating procedure
Computers and Operations Research
New Hybrid Discrete PSO for Solving Non Convex Trim Loss Problem
International Journal of Applied Evolutionary Computation
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We consider a stock cutting problem for a paper plant that produces sheets of various sizes for a finished goods inventory that services random customer demand. The controller decides when to shut down and restart the paper machine and how to cut completed paper rolls into sheets of paper. The objective is to minimize long-run expected average costs related to paper waste (from inefficient cutting), shutdowns, backordering, and holding finished goods inventory. A two-step procedure (linear programming in the first step and Brownian control in the second step) is developed that leads to an effective, but suboptimal, solution. The linear program greatly restricts the number of cutting configurations that can be employed in the Brownian analysis, and hence the proposed policy is easy to implement, and the resulting production process is considerably simplified. In an illustrative numerical example using representative data from an industrial facility, the proposed policy outperforms several policies that use a larger number of cutting configurations. Finally, we discuss some alternative production settings where this two-step procedure may be applicable.