Storage Location Allocation and Crane Scheduling Optimization in Automated Storage and Retrieval Systems with Dual I/O Ports.

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.