Efficient constraint handling in electromagnetism-like algorithm for traveling salesman problem with time windows.

Area of Science:

• Operations Research
• Computer Science
• Optimization

Background:

• The traveling salesman problem with time windows (TSPTW) is a complex optimization challenge.
• Existing methods struggle to efficiently handle time window constraints.

Purpose of the Study:

• To develop and evaluate a new electromagnetism-like algorithm (EMA) for TSPTW.
• To introduce a novel constraint handling technique for TSPTW.

Main Methods:

• An electromagnetism-like algorithm (EMA) framework was employed.
• A new variable bounding strategy combined with a penalty approach was used for constraint handling.
• The EMA's performance was benchmarked against state-of-the-art metaheuristics.

Main Results:

• The proposed EMA effectively minimizes travel costs in TSPTW problems.
• The novel constraint handling technique successfully eliminated time window violations.
• The EMA generated feasible and near-optimal solutions faster than competing algorithms.

Conclusions:

• The developed EMA is a highly effective method for solving TSPTW.
• The new constraint handling strategy significantly improves TSPTW solution feasibility and efficiency.