Application Of Genetic Algorithm On The Loading Problems
Overview of Loading Problems
In the current times, flexible manufacturing systems or FMSs has been adopted via many firms hence the rising requirement of customized production through high quality product and shorter lead times might be realized. The successful implementation and development of flexible manufacturing systems, prior needs addressing several problems. In flexible manufacturing systems, loading decisions involves a lot of tasks to be performed as like: operations of the chosen job allocated to the machine and the tool essential to perform these operations by satisfying technological constraints in order to make sure certain objectives including system unbalance and maximum throughput. The major post release issues that come under the purview of loading are:
a) Selection of part type;
b) Grouping of machines;
c) Determination of production ratio;
d) Batching of part types;
e) Allocation of pallets and fixtures; and
f) Allocation of tools and operations among machines.
Assignment of several resources like pallets, tools, fixtures etc to the already planned operations of different parts type falls into the category of the loading problems. In the loading problems, a decision that must interpret is considered like the tactical level planning decisions and inputs for them are the preceding decisions levels. These decisions levels generally contains grouping of resources, selection of part mixes and aggregate planning that provides the inputs for the consequent decisions of the dynamic operations planning and control. Hence, loading decisions can be considered to behave as a bridge among operation and strategic level decisions.