Abstract
An order picking system in a distribution centre consisting of parallel unidirectional picking lines is considered. The objectives are to minimise the walking distance of the pickers, the largest volume of stock on a picking line over all picking lines, the number of small packages, and the total penalty incurred for late distributions. The problem is formulated as a multi-objective multiple knapsack problem that is not solvable in a realistic time. Population-based algorithms, including the artificial bee colony algorithm and the genetic algorithm, are also implemented. The results obtained from all algorithms indicate a substantial improvement on all objectives relative to historical assignments. The genetic algorithm delivers the best performance.
Highlights
The supply chain of Pep Stores Ltd (PEP) is investigated in this study
The DBNs released for the present day, and the DBNs that are in the storage racks in the historical case, were used to determine whether the artificial bee colony (ABC) algorithm, genetic algorithm (GA), and memetic algorithm (MA) could assign a subset of these DBNs to the picking lines in a better way than was the historical case for that specific day
The DBNs released for the present day and the DBNs that are in the storage racks in the historical case were used to determine whether the ABC algorithm, GA, and MA could assign a subset of these DBNs to the picking lines in a better way than the historical case for that specific day
Summary
Author affiliations 1 Department of Logistics, University of Stellenbosch, South Africa. # The author was enrolled for an MCom (Operations Research) degree in the Department of Logistics, University of Stellenbosch. An order picking system in a distribution centre consisting of parallel unidirectional picking lines is considered. The objectives are to minimise the walking distance of the pickers, the largest volume of stock on a picking line over all picking lines, the number of small packages, and the total penalty incurred for late distributions. The genetic algorithm delivers the best performance. ’n Stelsel vir die opmaak van bestellings bestaande uit parallelle eenrigting uitsoeklyne in 'n distribusiesentrum word beskou. Al die algoritmes verkry ’n beduidende verbetering op historiese toewysings vir al die doelwitte.
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