IMPERIALIST COMPETITIVE ALGORITHM IS A WELL-KNOWN ALGORITHM IN THE FIELD OF OPTIMIZATION. THIS ALGORITHM IS PART OF COLLECTIVE INTELLIGENCE ALGORITHMS, WHICH HAS BEEN INSPIRED FROM CULTURAL, EDUCATIONAL AND POLITICAL INTERACTIONS BETWEEN COUNTRIES. IN THIS PAPER, IMPERIALIST COMPETITIVE ALGORITHM HAS BEEN USED FOR GLOBAL OPTIMIZATION IN STATIC AND CONTINUOUS ENVIRONMENTS. IN THE PROPOSED ALGORITHM, TO ADVANCE IN A BETTER POSITION, COUNTRIES OF EVERY COLONY ATTEMPT TO MOVE TOWARD A BETTER POSITION IN THE COLONY IN EACH ITERATION. THE USE OF CORRECTIONS APPROACH IN THE PROPOSED ALGORITHM HAS LED MANY COUNTRIES TO IMPROVE THEIR POSITION IN DIFFERENT ASPECTS BY BENEFITING FROM THE POSITIONS OF THE COLONISTS. THIS APPROACH HAS PROVIDED A BETTER GLOBAL SEARCH ABILITY AND PREVENTION FROM EARLY CONVERGENCE. TESTS CARRIED OUT IN TEN BENCHMARKS THAT ARE METRICS FOR MEASURING THE PERFORMANCE OF OPTIMIZATION ALGORITHMS INDICATE THE HIGH PERFORMANCE OF THE PROPOSED ALGORITHM.