Economic lot sizing: an O(n log n) algorithm that runs in linear time in the Wagner-Whitin case
Operations Research - Supplement
Improved algorithms for economic lot size problems
Operations Research
Applying the COMSOAL computer heuristic to the constrained resource allocation problem
Computers and Industrial Engineering
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Journal of Global Optimization
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Particle swarm optimization for integer programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Analysis of selection algorithms: A markov chain approach
Evolutionary Computation
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Computers and Industrial Engineering
Optimal scheduling of multiple dam system using harmony search algorithm
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Particle swarm optimization for tackling continuous review inventory models
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Stochastic lot-sizing with backlogging: computational complexity analysis
Journal of Global Optimization
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Minimizing resource consumption on uniform parallel machines with a bound on makespan
Computers and Operations Research
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We investigate the dynamic lot-size problem under stochastic and non-stationary demand over the planning horizon. The problem is tackled by using three popular heuristic methods from the fields of evolutionary computation and swarm intelligence, namely particle swarm optimization, differential evolution and harmony search. To the best of the authors' knowledge, this is the first investigation of the specific problem with approaches of this type. The algorithms are properly manipulated to fit the requirements of the problem. Their performance, in terms of run-time and solution accuracy, is investigated on test cases previously used in relevant works. Specifically, the lot-size problem with normally distributed demand is considered for different planning horizons, varying from 12 up to 48 periods. The obtained results are analyzed, providing evidence on the efficiency of the employed approaches as promising alternatives to the established Wagner-Whitin algorithm, as well as hints on their proper configuration.