Algoritmo de enxame de abelhas para resolução do problema da programação da produção Job Shop flexível multiobjetivo
Abstract
The production scheduling activity is considered as one of the most complex activities in
production management. This activity is part of the class of NP-Hard problems found in the
area of computer science, that is, those problems that can not be solved deterministically in
polynomial time. In addition, the complexity of this activity may increase according to the
constraints imposed on each programming system/problem. In this research, the problem
of programming of production the Flexible Job Shop (JSF) is studied. This problem is considered
an extension of the Job Shop programming problem. In JSF, a group of jobs (i.e.,
products, items, part of an item) formed by a set of operations and each operation must be
programmed by a resource (i.e., machine) that belongs to a group of resources that have the
same functional characteristics (e.g., cut, sanding, painting). This problem is characterized
in two sub-problems being routing and sequencing activity. Routing involves determining
which resource will process a given operation. Sequencing is the order in which each operation
will be processed on a resource. Through established programming, the objective of
this research is to optimize performance multicriteria: the makespan (i.e., time spent to produce
a set of jobs), processing time spent on the resource that worked by more time and total
production time. In order to reach the objectives mentioned above, a hybrid swarm approach
is proposed in this research. In this approach, two auxiliary methods are used to treat the
abovementioned sub-problems: genetic operator of mutation to perform the routing activity
and for the sequencing activity, an adaptive method of neighborhood structures is proposed.
In order to deal with the multiobjectivity of the problem, we propose the Pareto dominance
method. Experimental results obtained through commonly used benchmarks prove the efficacy
and superiority of the proposed approach when compared to other approaches also
applied to the problem studied.