JMetaBFOP: A tool for solving global optimization problems - Adrian García-López; Oscar Chávez-Bosquez; José Hernández-Torruco; Betania Hernández-Ocaña (SoftwareX, 2023)
The Two-Swim Modified Bacterial Foraging Optimization Algorithm (TS-MBFOA) is a bio-inspired algorithm that emulates the foraging behavior of E. Coli bacteria to solve optimization problems. JMetaBFOP (Bacterial foraging-based METAheuristics For Optimization Problems) is a framework implementing the TS-MBFOA processes as a library to solve optimization problems with preloaded constraints or defined by the end user. This paper presents the framework’s design using the Unified Modeling Language (UML), the implementation of a user interface (UI) in the Java platform, and the use of a mathematical expression evaluator called mXparser. JMetaBFOP allows faster calibration of TS-MBFOA parameters with the help of the UI; it eases the experimental design setup, visualization, and evaluation of feasible and optimal results for different optimization problems with constraints, such as benchmarks and particular problems. The framework was tested in 24 test problems with results: competitive in 14 problems, feasible in 7 ones, and no feasible solutions in 3 highly constrained problems. JMetaBFOP is an open-source project available on the GitHub platform.