Cluster structures influenced by interaction with a surface

2018 ◽  
Vol 20 (23) ◽  
pp. 15661-15670 ◽  
Author(s):  
Christopher Witt ◽  
Johannes M. Dieterich ◽  
Bernd Hartke
Keyword(s):  
Evolutionary Algorithms ◽  
Structure Optimization ◽  
Systematic Investigation ◽  
Global Structure

Systematic investigation of how cluster structures change upon interaction with a surface, using global structure optimization by evolutionary algorithms.

scholarly journals Global Commodity Chains and the New Imperialism

2019 ◽  
pp. 1-24 ◽  
Author(s):  
Intan Suwandi ◽  
R Jamil Jonna ◽  
John Bellamy Foster
Keyword(s):  
Multinational Corporations ◽  
World Economy ◽  
Systematic Investigation ◽  
Global Structure ◽  
First Century ◽  
Unequal Exchange ◽  
Value Transfer ◽  
Global Commodity Chains ◽  
New Imperialism

To comprehend twenty-first-century imperialism we must go beyond analysis of the nation-state to a systematic investigation of the increasing global reach of multinational corporations or the role of the global labor arbitrage. At issue is the way in which today's global monopolies in the center of the world economy have captured value generated by labor in the periphery within a process of unequal exchange, thus getting "more labour in exchange for less. The result has been to change the global structure of industrial production while maintaining and often intensifying the global structure of exploitation and value transfer.

scholarly journals A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms

2016 ◽  
Vol 24 (1) ◽  
pp. 183-203 ◽  
Author(s):  
Dogan Corus ◽  
Per Kristian Lehre ◽  
Frank Neumann ◽  
Mojgan Pourhassan
Keyword(s):  
Evolutionary Algorithms ◽  
Evolutionary Algorithm ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Global Structure ◽  
Number Of Clusters ◽  
Structure Representation ◽  
Fixed Parameter ◽  
Travelling Salesperson Problem ◽  
Parameterised Complexity

Bi-level optimisation problems have gained increasing interest in the field of combinatorial optimisation in recent years. In this paper, we analyse the runtime of some evolutionary algorithms for bi-level optimisation problems. We examine two NP-hard problems, the generalised minimum spanning tree problem and the generalised travelling salesperson problem in the context of parameterised complexity. For the generalised minimum spanning tree problem, we analyse the two approaches presented by Hu and Raidl ( 2012 ) with respect to the number of clusters that distinguish each other by the chosen representation of possible solutions. Our results show that a (1+1) evolutionary algorithm working with the spanning nodes representation is not a fixed-parameter evolutionary algorithm for the problem, whereas the problem can be solved in fixed-parameter time with the global structure representation. We present hard instances for each approach and show that the two approaches are highly complementary by proving that they solve each other’s hard instances very efficiently. For the generalised travelling salesperson problem, we analyse the problem with respect to the number of clusters in the problem instance. Our results show that a (1+1) evolutionary algorithm working with the global structure representation is a fixed-parameter evolutionary algorithm for the problem.

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