An evolutionary algorithm for the joint replenishment of inventory with interdependent ordering costs

Authors:
Anne Olsen
Affiliations:
Winthrop University, Rock Hill, SC
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Year:
2003

Citing 2
Cited 1

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An evolutionary algorithm for the joint replenishment problem

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Neuroevolutionary Inventory Control in Multi-Echelon Systems

ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory

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Abstract

The joint replenishment of inventory problem (JRP) requires independence of minor ordering costs. In this paper we propose an evolutionary algorithm (EA) for a modification of the JRP. The modified JRP allows for interdependence of minor ordering costs. Our proposed EA (EARP) is a nested EA that searches for a solution to minimize the total cost of inventory replenishment. It combines an EA which uses a direct grouping method with an EA_that uses an indirect grouping approach (EA_ind) by nesting EA ind inside EARP. We test EARP against partial enumeration and show that it provides close to optimal results for some problems. We know of no other algorithm to solve this problem.