A Novel Immune Algorithm for Multiparty Multiobjective Optimization

1. 1Identify the multiple decision makers and their objectives in the multiparty multiobjective optimization problem
2. 2Formulate the problem as a multiobjective optimization problem with multiple Pareto fronts
3. 3Apply the novel immune algorithm to search for a solution set that approximates the Pareto front of each decision maker
4. 4Evaluate the performance of the algorithm using metrics such as hypervolume and spread

This research benefits AI engineers and ML researchers working on multiobjective optimization problems, particularly in scenarios with multiple decision makers, by providing a new approach to finding Pareto optimal solutions

💡 The proposed algorithm can effectively handle multiple decision makers and their conflicting objectives, leading to better Pareto optimal solutions

🔍 Novel immune algorithm for multiparty multiobjective optimization! 🚀