6533b7d1fe1ef96bd125cf29
RESEARCH PRODUCT
A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding
Giada La ScaliaMario EneaGiuseppe Aiellosubject
Structure (mathematical logic)Mathematical optimizationClosenessGeneral EngineeringPareto principleSlicingComputer Science ApplicationsSet (abstract data type)Artificial IntelligenceEncoding (memory)Genetic algorithmMulti Objective Genetic Algorithm Facility Layout ProblemSlicing StructureMathematicsBlock (data storage)description
This paper proposes a new multi objective genetic algorithm (MOGA) for solving unequal area facility layout problems (UA-FLPs). The genetic algorithm suggested is based upon the slicing structure where the relative locations of the facilities on the floor are represented by a location matrix encoded in two chromosomes. A block layout is constructed by partitioning the floor into a set of rectangular blocks using guillotine cuts satisfying the areas requirements of the departments. The procedure takes into account four objective functions (material handling costs, aspect ratio, closeness and distance requests) by means of a Pareto based evolutionary approach. The main advantage of the proposed formulation, with respect to existing referenced approaches (e.g. bay structure), is that the search space is considerably wide and the practicability of the layout designs is preserved, thus improving the quality of the solutions obtained.
year | journal | country | edition | language |
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2012-09-01 | Expert Systems with Applications |