Drawer Algorithm: A New Metaheuristic Approach for Solving Optimization Problems in Engineering.

Area of Science:

• Computational Intelligence
• Optimization Theory
• Algorithm Design

Background:

• Metaheuristic algorithms are crucial for solving complex optimization problems.
• Existing algorithms may face challenges with exploration-exploitation balance and real-world constraints.

Purpose of the Study:

• Introduce a novel metaheuristic optimization algorithm, the Drawer Algorithm (DA).
• Evaluate the DA's effectiveness and efficiency in solving various optimization problems.

Main Methods:

• The Drawer Algorithm (DA) simulates selecting and combining items from different conceptual drawers.
• Mathematical modeling of the DA is presented.
• Performance evaluation using 52 objective functions, the CEC 2017 test suite, and 22 constrained problems from the CEC 2011 test suite.

Main Results:

• The DA achieves a good balance between exploration and exploitation, yielding suitable solutions.
• The DA demonstrates superior or competitive performance compared to twelve well-known optimization algorithms.
• The DA proves highly efficient in addressing constrained optimization problems relevant to real-world applications.

Conclusions:

• The Drawer Algorithm (DA) is a competitive and effective metaheuristic for optimization.
• The DA shows significant promise for tackling complex, real-world optimization challenges.