A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms

•We propose a bi-objective multi-product (r,Q) inventory.•We consider budget limitation and storage space in the model.•We present several multi-objective Pareto-based optimization algorithms.•The algorithms are compared with best-developed multi-objective algorithms. In this paper, a bi-objective m...

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Bibliographic Details
Published in:Applied soft computing Vol. 32; pp. 211 - 223
Main Authors: Fattahi, Parviz, Hajipour, Vahid, Nobari, Arash
Format: Journal Article
Language:English
Published: Elsevier B.V 01.07.2015
Subjects:
Continuous review
Inventory control
Multi-objective optimization
Pareto-based meta-heuristics
Inventory control
Continuous review
Multi-objective optimization
Pareto-based meta-heuristics
ISSN:1568-4946, 1872-9681
Online Access:Get full text
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Summary:•We propose a bi-objective multi-product (r,Q) inventory.•We consider budget limitation and storage space in the model.•We present several multi-objective Pareto-based optimization algorithms.•The algorithms are compared with best-developed multi-objective algorithms. In this paper, a bi-objective multi-product (r,Q) inventory model in which the inventory level is reviewed continuously is proposed. The aim of this work is to find the optimal value for both order quantity and reorder point through minimizing the total cost and maximizing the service level of the proposed model simultaneously. It is assumed that shortage could occur and unsatisfied demand could be backordered, too. There is a budget limitation and storage space constraint in the model. With regard to complexity of the proposed model, several Pareto-based meta-heuristic approaches such as multi-objective vibration damping optimization (MOVDO), multi-objective imperialist competitive algorithm (MOICA), multi-objective particle swarm optimization (MOPSO), non-dominated ranked genetic algorithm (NRGA), and non-dominated sorting genetic algorithm (NSGA-II) are applied to solve the model. In order to compare the results, several numerical examples are generated and then the algorithms were analyzed statistically and graphically.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2015.02.044