Imperialist Competitive Algorithm with Independence and Constrained Assimilation for Solving 0-1 Multidimensional Knapsack Problem

March 14, 2020 · Declared Dead · 🏛 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)

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Authors Ivars Dzalbs, Tatiana Kalganova, Ian Dear arXiv ID 2003.06617 Category cs.NE: Neural & Evolutionary Cross-listed cs.AI Citations 4 Venue 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) Last Checked 4 months ago

Abstract

The multidimensional knapsack problem is a well-known constrained optimization problem with many real-world engineering applications. In order to solve this NP-hard problem, a new modified Imperialist Competitive Algorithm with Constrained Assimilation (ICAwICA) is presented. The proposed algorithm introduces the concept of colony independence, a free will to choose between classical ICA assimilation to empires imperialist or any other imperialist in the population. Furthermore, a constrained assimilation process has been implemented that combines classical ICA assimilation and revolution operators, while maintaining population diversity. This work investigates the performance of the proposed algorithm across 101 Multidimensional Knapsack Problem (MKP) benchmark instances. Experimental results show that the algorithm is able to obtain an optimal solution in all small instances and presents very competitive results for large MKP instances.