Simultaneous Optimization of Storage Allocation and Routing Problems for Belt-conveyor Transportation

Abstract

Raw materials for industrial steel-making plants need to be stored in material yards in order to satisfy various production requirements. The stored materials are supplied to production plants by belt-conveyors with multiple alternative transportation routes. The simultaneous optimization of the storage allocation and transportation routing for the raw materials yard is required for achieving production that is flexible to changes in demand. In this paper, we propose a Lagrangian decomposition and coordination approach for storage allocation and routing for a belt-conveyor transportation system to handle demand changes. The overall problem is decomposed into an allocation planning subproblem and a transportation routing subproblem. A near-optimal solution for allocation planning and transportation routing is derived by repeating each optimization of subproblems and multiplier updates. The effectiveness of the proposed approach is confirmed in numerical experiments.

Planning an Integrated Stockyard–Port System for Smart Iron Ore Supply Chains via VND Optimization

“…Several studies related to stockyard-port planning using deterministic optimization techniques have been proposed in the last decade. Ago et al [13] proposed a Mixed-Integer Linear Programming (MILP) model with Lagrangian decomposition and coordination techniques to simultaneously optimize the storage allocation and transportation routing at the raw materials yard. Servare et al [14] developed a MILP (see Table 1) model and a linear relaxation-based heuristic to minimize the energy costs of an iron ore stockyard, including the production of mines and the demands of the berth.…”

Storage space allocation problem at inland bulk material stockyard

“…Most of the previous studies simplified the consideration of storage space allocation by allocating one material to one field (or so-called location), ignoring the capacity difference among the fields. Ago et al (2007) developed a Lagrangian decomposition approach to solve the storage allocation and routing problem for the stockyard in steel-making plants, aiming at allocating the materials to each stock area under the maximum capacity limit and determining the belt-conveyor transportation routes. Barros et al (2011) considered the stock level of the bulk materials in the stockyard when making the berth allocation decisions.…”

Improved efficiency of warehouse picking by co-optimization of order batching and storage location assignment

“…However, given that manual picking is still the mainstream in the collection of materials and products in warehouses, further efficiency improvement by using technology is necessary due to the increase in materials and products, and the decrease in working population. This issue is addressed by extensive investigations on optimization technology to improve the efficiency of various warehouse operations (Karásek, 2013) (Ago et al, 2007).…”