A Recombination-Based Tabu Search Algorithm for the Winner Determination Problem

Abstract. We propose a dedicated tabu search algorithm (TSX_WDP) for the winner determination problem (WDP) in combinatorial auctions. TSX_WDP integrates two complementary neighborhoods designed re-spectively for intensification and diversification. To escape deep local optima, TSX_WDP employs a backbone-based recombination opera-tor to generate new starting points for tabu search and to displace the search into unexplored promising regions. The recombination operator operates on elite solutions previously found which are recorded in an global archive. The performance of our algorithm is assessed on a set of 500 well-known WDP benchmark instances. Comparisons with five state of the art algorithms demonstrate the effectiveness of our approach

Memetic Algorithm for Solving the 0-1 Multidimensional Knapsack Problem

In this paper, we propose a memetic algorithm for the Multidimensional Knapsack Problem (MKP). First, we propose to combine a genetic algorithm with a stochastic local search (GA-SLS), then with a simulated annealing (GA-SA). The two proposed versions of our approach (GA-SLS and GA-SA) are implemented and evaluated on benchmarks to measure their performance. The experiments show that both GA-SLS and GA-SA are able to find competitive results compared to other well-known hybrid GA based approaches

Discriminate the response of Acute Myeloid Leukemia patients to treatment by using proteomics data and Answer Set Programming

International audienc