Introduction Documenting one's cumulative research program can be a humbling experience. First, such an assignment requires acknowledging that most of our work has limited impact on the academic and practitioner communities. Second, even setting impact aside, there is the issue of trying to make it appear that there is some master plan that guides our research. Here again, I suspect most of us ...

A variation of the channel assignment problem is naturally modeled by L(2, 1)-labelings of graphs. An L(2, 1)-labeling of a graph G is an assignment of labels from {0, 1, . . . , λ} to the vertices of G such that vertices at distance two get different labels and adjacent vertices get labels that are at least two apart and the λ-number λ(G) of G is the minimum value λ such that G admits an L(2, ...

The quadratic assignment problem (QAP) is very challengeable and interesting problem that can model many real-life problems. In this paper, we will simply discuss the meaning of quadratic assignment problem, solving techniques and we will give a survey of some developments and researches.

It was recently demonstrated that a well-known eigenvalue bound for the Quadratic Assignment Problem (QAP) actually corresponds to a semideenite programming (SDP) relaxation. However, for this bound to be computationally useful the assignment constraints of the QAP must rst be eliminated, and the bound then applied to a lower-dimensional problem. The resulting \projected eigenvalue bound" is on...

We describe a new convex quadratic programming bound for the quadratic assignment problem (QAP). The construction of the bound uses a semideenite programming representation of a basic eigenvalue bound for QAP. The new bound dominates the well-known projected eigenvalue bound, and appears to be competitive with existing bounds in the tradeoo between bound quality and computational eeort.

This paper reports heuristic and exact solution advances for the Quadratic Assignment Problem (QAP). QAP instances most often discussed in the literature are relatively well solved by heuristic approaches. Indeed, solutions at a fraction of one percent from the best known solution values are rapidly found by most heuristic methods. Exact methods are not able to prove optimality for these instan...

This paper considers a mass transit system in a regional area. The problem of improving the quality of the service in terms of costs perceived by the passenger is studied. A model to improve the effectiveness of the system maintaining the feasibility of the traffic assignment is proposed, along with new definitions of passenger assignment to support the proposed model.

Local search procedures are popular methods to solve combinatorial problems and neighborhood structures are the main part of those algorithms. This paper presents a new neighborhood for the Quadratic Assignment Problem. The proposed neighborhood is compared with the classical 2-exchange neighborhood.

We consider transformations of the (metric) Quadratic Assignment Problem (QAP), that exploit the metric structure of a given instance. We show in particular, how the structural properties of rectangular grids can be used to improve a given lower bound. Our work is motivated by previous research of G.S. Palubetskes, and it extends a bounding approach proposed by J. Chakrapani and J. Skorin-Kapov...