Storage Location Allocation and Crane Scheduling Optimization in Automated Storage and Retrieval Systems with Dual...

This paper addresses the challenge of integrated optimization for storage space allocation and crane scheduling in Automated Storage and Retrieval Systems (AS/RSs) under the complex constraints of dual I/O ports and Shared Storage strategies. The scheduling of multi-shuttle cranes in such environments constitutes a highly coupled NP-hard combinatorial optimization problem, where task assignment, sequencing, and dynamic storage location allocation must be solved simultaneously. To tackle this, this paper proposes an Elite-Driven Synchronized-Repair Memetic Algorithm (ED-SRMA) based on a sensor-informed total-travel-time objective formulated from horizontal and vertical crane displacements that can be measured by the crane drive sensors. The method combines a dual-layer representation, cross-layer synchronization, a problem-specific feasibility-repair operator, elite preservation, and budgeted local refinement. Numerical experiments were conducted on seven problem scales using 30 paired independent runs and a fixed evaluation budget. Compared with the corresponding dual-I/O operating mode without immediate location reuse, the shared-storage RS mode reduced the mean total travel time by 4.57-14.89%. ED-SRMA reduced the mean objective value by 5.48-39.59% relative to Base-GA and by 3.99-28.82% relative to PSO. For the representative 120×5 instance, the fitness-evaluation-based convergence analysis further shows an earlier objective-value reduction and continued improvement under the common evaluation budget. These results demonstrate the effectiveness, statistical significance, and consistency under the tested conditions of ED-SRMA for the investigated dual-I/O shared-storage scheduling problem.