In this paper, we study the exploration / exploitation trade-off in cellular genetic algorithms. We define a new selection scheme, the centric selection, which is tunable and allows controlling the selective pressure with a single parameter. The equilibrium model is used to study the influence of the centric selection on the selective pressure and a new model which takes into account problem de...

In this paper, we discuss analog neural approaches to the quadratic assignment problem (QAP). These approaches employ a hard constraints scheme to restrict the domain space, and are able to obtain much improved solutions over conventional neural approaches. Since only a few strong heuristics for QAP have been known to date, our approaches are good alternatives, capable of obtaining fairly good ...

The Max-Profit Generalized Assignment Problem (Max-GAP) is: given sets J of bins and I of items, where each j ∈ J has capacity c(j) and each i ∈ I has in bin j size `(i, j) and profit p(i, j), find a maximum profit feasible assignment. The problem admits a 1/2-approximation algorithm. Our main result is a (1− 1/e)-approximation algorithm for Max-GAP with fixed profits when each i ∈ I has a fixe...

Let A = {a1, a2, . . . , as} and {b1, b2, . . . , bt} be two sets of objects with s + r = n, the generalized assignment problem assigns each element ai ∈ A to at least αi and at most α ′ i elements in B, and each element bj ∈ B to at least βj and at most β ′ j elements in A for all 1 ≤ i ≤ s and 1 ≤ j ≤ t. In this paper, we present an O(n) time and O(n) space algorithm for this problem using th...

this paper deals with the problem of user-server assignment in online social network systems. online social network applications such as facebook, twitter, or instagram are built on an infrastructure of servers that enables them to communicate with each other. a key factor that determines the facility of communication between the users and the servers is the expected transmission time (ett). a ...

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New lower bounds for the quadratic assignment problem QAP are presented. These bounds are based on the orthogonal relaxation of QAP. The additional improvement is obtained by making eecient use of a tractable representation of orthogonal matrices having constant row and column sums. The new bound is easy to implement and often provides high quality bounds under an acceptable computational eeort.

It is the purpose of this paper to propose and discuss certain modifications of the ideas concerning GromovHausdorff distances in order to tackle the problems of shape matching and comparison. These reformulations render these distances more amenable to practical computations without sacrificing theoretical underpinnings. A second goal of this paper is to establish links to several other practi...

We give a (1 − 1/e)-approximation algorithm for the Max-Profit Generalized Assignment Problem (Max-GAP) with fixed profits when the profit (but not necessarily the size) of every item is independent from the bin it is assigned to. The previously best known approximation ratio for this problem was 1/2. Key-words. Generalized assignment, Approximation algorithm.

We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard, S.E. Karisch, F. Rendl. QAPLIB — a quadratic assignment problem library. Journal on Global Optimiza...