A Generalized Cell Formation Problem Solved by an Adapted Gga

This paper addresses the cell formation problem with alternative process plans and machine capacity constraints. The problem of Generalized Cell Formation consists in defining the preferential process and the preferential routing for each part optimizing the grouping of machines into independent manufacturing cells. The problem is reduced in two grouping problems: grouping operations (including the selection of process and routing) into machines (yielding flows between the machines) and grouping machines into cells. To solve these two interdependent grouping problems, we proposed an adapted grouping genetic algorithm (SIGGA). The chromosome is composed by two parts encoding both problems. The encoding is based on group encoding. The genetic operators are focalized on groups instead of treated objects. These operators are applied on both part of the chromosome to simultaneously evolve the population on both grouping problems. The used heuristics and operator are fully detailed. The algorithm has been tested on four literature cases presented by Sofianopoulou.