A comparative study on economic production quantity (EPQ) model under space constraint with different kinds of data

Abstract

Purpose

The purpose of this paper is to develop a multi-item economic production quantity (EPQ) strategy under grey environment and space constraint. Since the “demand” cannot be predicted with certainty, it is assumed that data behave under grey environment and compare the proposed inventory model with other studies using crisp or fuzzy environments.

Design/methodology/approach

This paper is to optimise the cycle time and total cost of the multi-item EPQ inventory model. For this purpose, the Lagrangian coefficient is used to solve the constrained optimisation problem. The grey relational analysis approach and grey data are applied in developing the EPQ inventory model.

Findings

The results are compared with the analysis using crisp and fuzzy data. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The results of the study demonstrate that crisp data outperform the other two data in all scales problems in terms of cycle time and cost; grey data perform better in all scales problems than fuzzy data.

Originality/value

The contribution of this research is the use of grey data in developing the EPQ inventory model with space constraint.

Citation

Karbassi Yazdi, A., Kaviani, M.A., Sarfaraz, A.H., Cárdenas-Barrón, L.E., Wee, H.-M. and Tiwari, S. (2019), "A comparative study on economic production quantity (EPQ) model under space constraint with different kinds of data", Grey Systems: Theory and Application, Vol. 9 No. 1, pp. 86-100. https://doi.org/10.1108/GS-08-2018-0035