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An introduction is presented in which the editor discusses articles in the issue on topics including global optimization, mathematical optimization, and linear optimization.

The article focuses on several studies related to the concepts of satisfiability, Boolean modeling and computation. One study described disjunctive normal form (DNF) tautologies with terms conflicting in one or two variables pairwise and possessing a tree-like structure. Another study proposed a semidefinite programming relaxation for the satisfiability problem. A third study discussed theoretical and experimental results on the use of satisfiability problem (SAT) algorithms for colouring special classes of graphs.

We present a new framework for efficiently finding competitive solutions for the facility-layout problem. This framework is based on the combination of two new mathematical-programming models. The first model is a relaxation of the layout problem and is intended to find good starting points for the iterative algorithm used to solve the second model. The second model is an exact formulation of the facility-layout problem as a nonconvex mathematical program with equilibrium constraints (MPEC). Aspect ratio constraints, which are frequently used in facility-layout methods to restrict the occurrence of overly long and narrow departments in the computed layouts, are easily incorporated into this new framework. Finally, we present computational results showing that the complete framework can be solved efficiently using widely available optimization software, and the resulting layouts improve on those obtained using previous approaches in the literature. Moreover, the framework can be used to find different competitive layouts with relatively little computational effort, which is advantageous for a user who wishes to consider several competitive layouts rather than simply using a mathematically optimal layout. [ABSTRACT FROM AUTHOR]

Abstract: The facility layout problem is concerned with the arrangement of a given number of rectangular facilities so as to minimize the total cost associated with the (known or projected) interactions between them. We consider the one-dimensional space-allocation problem (ODSAP), also known as the single-row facility layout problem, which consists in finding an optimal linear placement of facilities with varying dimensions on a straight line. We construct a semidefinite programming (SDP) relaxation providing a lower bound on the optimal value of the ODSAP. To the best of our knowledge, this is the first non-trivial global lower bound for the ODSAP in the published literature. This SDP approach implicitly takes into account the natural symmetry of the problem and, unlike other algorithms in the literature, does not require the use of any explicit symmetry-breaking constraints. Furthermore, the structure of the SDP relaxation suggests a simple heuristic procedure which extracts a feasible solution to the ODSAP from the optimal matrix solution to the SDP relaxation. Computational results show that this heuristic yields a solution which is consistently within a few percentage points of the global optimal solution. [Copyright &y& Elsevier]