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Multi-objective particle swarm optimisation approach for production-inventory control systems

journal contribution
posted on 20.03.2019, 00:00 by Huthaifa Al-Khazraji, Colin Cole, Wanwu Guo
Purpose: This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach: The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings: The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications: This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value: PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems. © 2018, Emerald Publishing Limited.

Funding

Category 3 - Industry and Other Research Income

History

Volume

13

Issue

4

Start Page

1037

End Page

1056

Number of Pages

20

eISSN

1746-5672

ISSN

1746-5664

Publisher

Emerald Publishing, UK

Peer Reviewed

Yes

Open Access

No

Acceptance Date

20/08/2018

Author Research Institute

Centre for Railway Engineering

Era Eligible

Yes

Journal

Journal of Modelling in Management

Exports

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