iMOPSE: a Comprehensive Open Source Library for Single- and Multi-objective Metaheuristic Optimization

The Intelligent Multi-Objective Problem Solving Environment (iMOPSE) is a robust open-source C++ library designed to tackle NP-hard optimization problems. It hosts a suite of multi-objective optimization algorithms, including state-of-the-art NSGA-II, MOEA/D, SPEA2, or NTGA2, complemented by a set of single-objective optimization metaheuristics such as Genetic Algorithms, Differential Evolution, Ant Colony Optimization, Tabu Search, Simulated Annealing, and Particle Swarm Optimization. One of iMOPSE’s notable strengths lies in its ability to handle classical NP-hard problems with constraints, ranging from the Traveling Salesman and Traveling Thief to Capacitated Vehicle Routing and Multi-Skill Resource-Constrained Project Scheduling Problems. Its flexible encoding mechanism adeptly manages different problems and facilitates the utilization of specialized operators. Moreover, iMOPSE offers pre-configured problem instances and method setups, along with a suite of tools for data collection, visualization, and analysis, bolstering its efficacy for rigorous research and optimization result interpretation. iMOPSE also provides extensive customization options, enabling researchers to explore and research various optimization methods and scenarios effectively. Its user-friendly interface streamlines setup procedures through intuitive input parameters and configuration files, ensuring accessibility across Windows and Unix-based operating systems. Together, these features position iMOPSE as a comprehensive solution for addressing real-world optimization challenges.