A Bi-Level Bi-Objective optimization model for the integrated storage classes and dual shuttle cranes scheduling in AS/RS with energy consumption, workload balance and time windows

• Published in: Journal of cleaner production Vol. 257; p. 120409
• Main Authors: Habibi Tostani, H., Haleh, H., Hadji Molana, S.M., Sobhani, F.M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2020
• Subjects: algorithms; automation; Crane scheduling; energy; inventories; issues and policy; Location assignment; Meta-heuristic; planning; Warehousing; Crane scheduling; Meta-heuristic; Warehousing; Location assignment
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2020.120409

Dual shuttle cranes scheduling problem is an option of Automated Storage and Retrieval System (AS/RS), which has paid marginal academic regard, so it could be extended to advance novel challenges that should be investigated. In this paper, an integrated class-based storage location assignment and dual shuttle cranes scheduling problem is addressed by introducing a novel bi-level optimization model. In the upper-level, the locations of storing and retrieving products under class-based storage policy, multi-period planning and inventory considerations are determined, which its objective functions are included minimization of total cost and energy consumption. The solution of this level is utilized by the lower-level, which is related to the scheduling of dual shuttle cranes. In the lower-level, a broad range of necessities of rewarding scheduling, ranging from workload balance to time windows under multi-period planning is reflected. Since the proposed model is a bi-level and bi-objective, a Modified Cooperative Coevolutionary Algorithm for Bi-Level Optimization (MCoBRA) is presented with the intention of solving the proposed model. Finally, in order to illustrate the validation of the proposed model and solution approach, a broad range of numerical experiments are sketched out, and some comparative analyses concerning two existing algorithms in the literature are provided. Sensitivity analyses show that considering class-based storage policy in the upper-level has significant influences on the whole of the objective functions, which could be offered better planning of operations.