Optimization models and algorithms for multi-period cutting stock Problems

Many manufacturing companies face production planning problems. Decisions that need to be taken over multiple periods include when and how much to produce of specific products, so that demand is satisfied. In this project we consider a complex production process, in which items with a customized length need to be cut from bigger objects with a standard length (which is known as the Cutting Stock Problem). Such cutting processes are typically found in the steel, paper and wood processing industry. In the light of growing competitiveness, environmental responsibility and lack of natural resources, it is important to efficiently plan this cutting process in order to use scarce resources in the most efficient way, so that waste and other costs are minimized. The aim of the research is to develop novel heuristic solution approaches for several variants of this problem. The methodology is based on mathematical modelling and heuristic optimization techniques with the objective to provide high-quality solutions (i.e., production plans) for large instances of the problem (i.e., with many end products and a large time horizon) in a short computation time.

Faculty Supervisor:

Raf Jans

Student:

Partner:

Universidade Estadual Paulista "Julio de Mesquita Filho"

Discipline:

Business

Sector:

Advanced Manufacturing; Artificial Intelligence

University:

HEC Montréal

Program: