Mathematical Programming: Series A and B
Machine layout problem in flexible manufacturing systems
Operations Research
Methods for the one-dimensional space allocation problem
Computers and Operations Research
The cut polytope and the Boolean quadric polytope
Discrete Mathematics
A new heuristic for the linear placement problem
Computers and Operations Research
Some simplified NP-complete problems
STOC '74 Proceedings of the sixth annual ACM symposium on Theory of computing
A new lower bound for the single row facility layout problem
Discrete Applied Mathematics
An Exact Approach to the One-Dimensional Facility Layout Problem
Operations Research
Solving Max-Cut to optimality by intersecting semidefinite and polyhedral relaxations
Mathematical Programming: Series A and B
Provably near-optimal solutions for very large single-row facility layout problems
Optimization Methods & Software - GLOBAL OPTIMIZATION
Exact Algorithms for the Quadratic Linear Ordering Problem
INFORMS Journal on Computing
Speeding up IP-based algorithms for constrained quadratic 0–1 optimization
Mathematical Programming: Series A and B - Series B - Special Issue: Combinatorial Optimization and Integer Programming
Note: A polyhedral study of triplet formulation for single row facility layout problem
Discrete Applied Mathematics
A scatter search algorithm for the single row facility layout problem
Journal of Heuristics
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The single-row facility layout problem (SRFLP) is an NP-hard combinatorial optimization problem that is concerned with the arrangement of n departments of given lengths on a line so as to minimize the weighted sum of the distances between department pairs. (SRFLP) is the one-dimensional version of the facility layout problem that seeks to arrange rectangular departments so as to minimize the overall interaction cost. This paper compares the different modelling approaches for (SRFLP) and applies a recent SDP approach for general quadratic ordering problems from Hungerländer and Rendl to (SRFLP). In particular, we report optimal solutions for several (SRFLP) instances from the literature with up to 42 departments that remained unsolved so far. Secondly we significantly reduce the best known gaps and running times for large instances with up to 110 departments.