6,209 research outputs found
A Weight-coded Evolutionary Algorithm for the Multidimensional Knapsack Problem
A revised weight-coded evolutionary algorithm (RWCEA) is proposed for solving
multidimensional knapsack problems. This RWCEA uses a new decoding method and
incorporates a heuristic method in initialization. Computational results show
that the RWCEA performs better than a weight-coded evolutionary algorithm
proposed by Raidl (1999) and to some existing benchmarks, it can yield better
results than the ones reported in the OR-library.Comment: Submitted to Applied Mathematics and Computation on April 8, 201
Cosolver2B: An Efficient Local Search Heuristic for the Travelling Thief Problem
Real-world problems are very difficult to optimize. However, many researchers
have been solving benchmark problems that have been extensively investigated
for the last decades even if they have very few direct applications. The
Traveling Thief Problem (TTP) is a NP-hard optimization problem that aims to
provide a more realistic model. TTP targets particularly routing problem under
packing/loading constraints which can be found in supply chain management and
transportation. In this paper, TTP is presented and formulated mathematically.
A combined local search algorithm is proposed and compared with Random Local
Search (RLS) and Evolutionary Algorithm (EA). The obtained results are quite
promising since new better solutions were found.Comment: 12th ACS/IEEE International Conference on Computer Systems and
Applications (AICCSA) 2015. November 17-20, 201
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