Solving Zero-Wait Problems in Production Scheduling Using Clonal Selection Algorithm from Immune Algorithms

This document discusses the application of clonal selection algorithm from immune algorithms to solve zero-wait problems in production scheduling. The clonal selection algorithm is an optimization technique based on immunological principles that mimics the clonal expansion and mutation processes in immune systems to search for optimal solutions. Key implementation aspects include antibody population initialization, affinity calculation using scheduling objectives, cloning proportional to affinity values, hypermutation operators for solution diversity, and selection mechanisms for maintaining population quality. Experimental results demonstrate the algorithm's effectiveness in handling zero-wait constraints where consecutive operations must proceed without delays. The implementation typically involves encoding scheduling solutions as antibody representations, with fitness functions evaluating makespan or throughput objectives while penalizing wait-time violations. I welcome constructive feedback and technical discussions on the algorithmic approach and code implementation to further enhance its performance and expand applicability to broader production scheduling scenarios.