Books.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
Overview
The book considers the lot-sizing and scheduling problem for flexible flow line production facilities. Flexible flow lines are flow lines with parallel machines on some or all production stages. They can be found in a vast number of industries. A three-phased solution approach is presented that solves the integrated lot-sizing and scheduling problem in a hierarchical manner. The approach is able to handle several important features relevant in industrial practice, such as back-orders and setup carry-over. The developed solution procedures solve practically sized problems in a relatively short amount of time. One of the procedures is based on a novel mixed integer programming (MIP) model, which employs integer variables instead of binary variables. This makes it possible to find (near-)optimal solutions using standard algorithms such as CPLEX. Another procedure uses two nested Genetic Algorithms. An application of the framework in the semiconductor industry is given.
Synopsis
The book considers the lot-sizing and scheduling problem for flexible flow line production facilities. Flexible flow lines are flow lines with parallel machines on some or all production stages. They can be found in a vast number of industries. A three-phased solution approach is presented that solves the integrated lot-sizing and scheduling problem in a hierarchical manner. The approach is able to handle several important features relevant in industrial practice, such as back-orders and setup carry-over. The developed solution procedures solve practically sized problems in a relatively short amount of time. One of the procedures is based on a novel mixed integer programming (MIP) model, which employs integer variables instead of binary variables. This makes it possible to find (near-)optimal solutions using standard algorithms such as CPLEX. Another procedure uses two nested Genetic Algorithms. An application of the framework in the semiconductor industry is given.