Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem
This is an incremental theoretical analysis for researchers in evolutionary optimization, focusing on a specific combinatorial problem.
The paper theoretically analyzes a multiobjective evolutionary algorithm for the 0-1 knapsack problem, comparing local search and greedy search initialization methods and evaluating solution quality using approximation ratios.
Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation and greedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.