An ε-accurate model for optimal unequal-area block layout design
Computers and Operations Research
A New Mathematical-Programming Framework for Facility-Layout Design
INFORMS Journal on Computing
Optimal layout and work allocation in batch assembly under learning effect
International Journal of Intelligent Systems Technologies and Applications
Optimal solution for the two-dimensional facility layout problem using a branch-and-bound algorithm
Computers and Industrial Engineering
Heterogeneous Architecture Exploration: Analysis vs. Parameter Sweep
ARC '09 Proceedings of the 5th International Workshop on Reconfigurable Computing: Architectures, Tools and Applications
Solving Lot-Sizing Problems on Parallel Identical Machines Using Symmetry-Breaking Constraints
INFORMS Journal on Computing
A new optimization model to support a bottom-up approach to facility design
Computers and Operations Research
Expert Systems with Applications: An International Journal
Efficient Heterogeneous Architecture Floorplan Optimization using Analytical Methods
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
A genetic algorithm with the heuristic procedure to solve the multi-line layout problem
Computers and Industrial Engineering
Applying the sequence-pair representation to optimal facility layout designs
Operations Research Letters
A new mixed integer programming formulation for facility layout design using flexible bays
Operations Research Letters
Multiobjective layout optimization of robotic cellular manufacturing systems
Computers and Industrial Engineering
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This paper presents an improved mixed-integer programming (MIP) model and effective solution strategies for the facility layout problem and is motivated by the work of Meller et al. (1999). This class of problems seeks to determine a least-cost layout of departments having various size and area requirements within a rectangular building, and it is challenging even for small instances. The difficulty arises from the disjunctive constraints that prevent departmental overlaps and the nonlinear area constraints for each department, which existing models have failed to approximate with adequate accuracy. We develop several modeling and algorithmic enhancements that are demonstrated to produce more accurate solutions while also decreasing the solution effort required. We begin by deriving a novel polyhedral outer approximation scheme that can provide as accurate a representation of the area requirements as desired. We also design alternative methods for reducing problem symmetry, evaluate the performance of several classes of valid inequalities, explore the construction of partial convex hull representations for the disjunctive constraints, and investigate judicious branching variable selection priority schemes. The results indicate asubstantial increase in the accuracy of the layout produced, while at the same time providing adramatic reduction in computational effort. In particular, three previously unsolved test problems from the literature for which Meller et al.'s algorithm terminated prematurely after 24 cpu hours of computation (on a SUN Ultra 2 workstation with 390 MB RAM) with respective optimality gaps of 10.14%, 26.45%, and 40%, have been solved to exact optimality with reasonable effort using our proposed approach.