Title: Integrating shelving technology selection and storage assignment under uncertainty: a two-stage mathematical programming approach

Authors: Mohammadreza Farhadi Moghadam; Kaveh Khalili Damghani; Vahidreza Ghezavati; Alireza Rashidi Komijan

Addresses: Department of Industrial Engineering, S.T.C. Islamic Azad University, Tehran, Iran ' Department of Industrial Engineering, S.T.C. Islamic Azad University, Tehran, Iran ' Department of Industrial Engineering, S.T.C. Islamic Azad University, Tehran, Iran ' Department of Industrial Engineering, S.R.C. Islamic Azad University, Tehran, Iran

Abstract: The primary objective of this study is to select appropriate shelving technology while minimising intra warehouse transportation costs under probabilistic demand conditions. This research introduces four key innovations: integrating shelving technology selection and storage location assignment problem for the first time, considering capacity as a probabilistic variable to enhance realism, incorporating a multi-period framework, and allowing replenishment. Since predicting required capacity deterministically for shelving technology selection is impractical, capacity is modelled as a probabilistic variable. The next step involves allocating items to this technology. The problem is designed as multi-periodic, where, in each period, some orders are dispatched to customers, and some items are stored in the system. The problem ensures that sufficient space is always available for incoming items, forming a combined warehouse design and item allocation problem for shelving technology. Failure to address these integrative issues can lead to suboptimal solutions. A two-stage programming approach is employed to solve the model. Given the probabilistic nature of required capacity, the problem is solved under both continuous and discrete conditions, and a comparison between these approaches is conducted to determine the most effective solution method.

Keywords: warehouse design; shelving technology; storage location assignment problem; probabilistic method.

DOI: 10.1504/IJMDM.2026.154611

International Journal of Management and Decision Making, 2026 Vol.25 No.4, pp.331 - 359

Received: 12 May 2025
Accepted: 17 Oct 2025
Published online: 07 Jul 2026 *

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