Multi-objective optimization using genetic simulated annealing algorithm

In many real-life problems, objectives under consideration conflict with,each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. In this paper, an overview and tutorial is presented describing genetic simulated annealing algorithm (GSAA) developed specifically for problems with 0/1 knapsack problem. Experimental results have shown that GSAA is superior to genetic algorithm (GA) and simulated annealing (SA) on performance.