Shivali Lomate
Dr. B Rajiv
Dr. PD Pantawane
Prof. BB Ahuja
Abstract
The efficient utilization of raw material is utmost important for the manufacturing plants in order to reduce material wastage and cost of production. Cutting stock problem (CSP) deals with cutting of small objects (finals), out of a larger one exhibits the problem of minimization of wastage of material and optimal utilization of space. The design of Pattern which is a unique combination of finals is a very tricky and have several wellestablished methods. However, there are no general and efficient method that is applicable to CSP since it is NP-hard problem. In this paper a novel hybrid approach to solve CSP has been develop and proposed. CSP problem has been decomposed in two parts viz. Pattern Generation and Optimization. Pattern Generation is done by Greedy Optimization and optimization is done by integer programming. This paper present solution for 1D-CSP and 2D-CSP using hybrid approach and deals with several case studies and sample problems to showcase the applicability of this hybrid solution. It is worthwhile to mention that this approach solves the CSP problem in minimum given time and presents quality solutions. CSP is decompose in two parts in which patterns generation is done by Greedy Algorithm and Optimization is done using Integer Programming. This novel approach to solve CSP problem shows that its performance is better in terms of quality of solution and time required to solve the problem viz-a-viz existing solutions available.Keywords- Cutting stock problem, Raw, Final, Pattern, NP-hard problem, greedy algorithm, integer programming