Optimizing Resource-Constrained Scheduling in Materials Manufacturing Using an Improved Genetic Algorithm

Efficient scheduling in materials manufacturing environment plays a crucial role in minimizing idle time, increasing throughput, and making better use of limited resources. This paper introduces a Genetic Algorithm enhanced with Guided Mutation (GA-GM) to address resource-constrained scheduling challenges in fabrication workflows such as composite forming, thermal processing, and experimental materials analysis. The algorithm refines operation sequences by resolving conflicts arising from shared machinery and limited material availability. Experimental comparisons with traditional heuristics confirm that GA-GM delivers reduced processing durations and improved resource efficiency.