Cutting stock problem: A solution based on novel pattern based chromosome representation using modified GA

The cutting stock problem (CSP) is an important problem in class of combinatorial optimization problems because of its NP-hard nature. Cutting the required material from available stock with minimum wastage is a challenging process in many manufacturing industries such as rod industry, paper industry, textile industry, wood industry, plastic and leather manufacturing industry etc. This objective of this research work is to Propose Novel Pattern based chromosome representation using Modified Genetic Algorithm for multiple stock size cutting stock problem (MSSCSP) and Single stock size cutting stock problem (SSSCSP). The main challenge in solving cutting stock problem is to develop chromosome representation for MSSCSP in GA. Moreover, this paper Test results on 20 large dataset with LP, EP and Two-swap algorithm. Our Propose algorithm gives better results than LP in MSSCSP, EP in SSSCSP and Two-swap algorithm in SSSCSP.

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