A Relative Comparison between BAP and JSSP using Two Heuristics AFSA and ACO

Scheduling is the allocation of shared resources over time to competing activities. Job Shop Scheduling Problem (JSSP) and Berth Scheduling or Berth Allocation Problem (BAP) is two of NP-Complete problems in Operations research. BAP can be modeled as an unrelated parallel machine-scheduling problem (Pinedo, 2002), where a vessel is treated as a job and a berth as a machine. Thus JSSP and BAP are related with each other and solved using two different Meta heuristics. The Ant colony Optimization (ACO) is used to solve JSSP and Artificial Fish Schooling Algorithm (AFSA) is used to solve BAP. The experimental results are compared. The performance evaluation shows, the AFSA converges more quickly than ACO.