VLSI cell placement techniques
ACM Computing Surveys (CSUR)
Enhanced Model Formulations for Optimal Facility Layout
Operations Research
Optimal solution for the two-dimensional facility layout problem using a branch-and-bound algorithm
Computers and Industrial Engineering
Computers and Industrial Engineering
A particle swarm optimization for the single row facility layout problem
Computers and Industrial Engineering
A simulated annealing heuristic for the dynamic layout problem with budget constraint
Computers and Industrial Engineering
Orthogonal packing of identical rectangles within isotropic convex regions
Computers and Industrial Engineering
Computers and Industrial Engineering
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Applying the sequence-pair representation to optimal facility layout designs
Operations Research Letters
VLSI module placement based on rectangle-packing by the sequence-pair
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
GORDIAN: VLSI placement by quadratic programming and slicing optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Simultaneous Floor Planning and Global Routing for Hierarchical Building-Block Layout
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Modern floorplanning based on B*-tree and fast simulated annealing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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This paper proposes a multiobjective layout optimization method for the conceptual design of robot cellular manufacturing systems. Robot cellular manufacturing systems utilize one or more flexible robots which can carry out a large number of operations, and can conduct flexible assemble processes. The layout design stage of such manufacturing systems is especially important since fundamental performances of the manufacturing system under consideration are determined at this stage. In this paper, the design criteria for robot cellular manufacturing system layout designs are clarified, and objective functions are formulated. Next, layout design candidates are represented using a sequence-pair scheme to avoid interference between assembly system components, and the use of dummy components is proposed to represent layout areas where components are sparse. A multiobjective genetic algorithm is then used to obtain Pareto optimal solutions for the layout optimization problems. Finally, several numerical examples are provided to illustrate the effectiveness and usefulness of the proposed method.