Modeling of Scheduling Algorithms with Alternative Process Plans in an Optimization Programming Language
This thesis optimizes scheduling functions with alternative processes for manufacturing features. The problem considered is an N job – M methods problem, where each feature can be processed in up to M methods. Linear and polynomial models have been built in Optimization Language (OPL) to optimize the make span without setup times. The user is provided an interface in Java to enter the system parameters, generate the data file, choose the OPL model and execute the model. This thesis concludes that in the absence of heuristics, linear model performs better than a non-linear model for the same problem and combining system parameters intelligently gives a better chance of solving the problem faster.
School Location:USA - Ohio
Source Type:Master's Thesis
Keywords:scheduling process planning optimization opl mathematical modeling linear and non models
Date of Publication:01/01/2004