Buffer size optimization in asynchronous assembly systems using genetic algorithms
Computers and Industrial Engineering
Ant algorithms for discrete optimization
Artificial Life
Simulation optimization: a survey of simulation optimization techniques and procedures
Proceedings of the 32nd conference on Winter simulation
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Ant Colony Optimization
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This paper presents an algorithm for the near-optimal allocation of buffer space to an assembly line by means of the ant colony optimisation (ACO) paradigm. Uniquely, the algorithm has been designed to work in conjunction with a simulation model and is adapted to have both combinatorial and stochastic problem-solving capability. The simulation model was developed using the WITNESS simulation package and serves the purpose of an objective function evaluator, encapsulating the dynamics of the line and enabling the production rate for a particular buffer configuration to be determined. Finally, the WITNESS Optimiser module was used as a benchmark in validating the ACO algorithm's performance. In the simulation experiments conducted, ACO attained slightly better results overall.