Abstract
Short-term scheduling of batch polymer plant involves the scheduling of different orders in parallel available production lines. The scheduling becomes more challenging due to the presence of sequence-dependent changeover constraints between different orders which lead to combinatorial optimization formulation. Such combinatorial optimization problems have exponential time complexity on the silicon-based computer. DNA computing experiments are found to be promising for such combinatorial optimization problems particularly involving unique feasible optimal solution. However, use of DNA to find a solution to real-life problems involving multiple feasible solutions is an emerging area of research. The present paper illustrates the DNA solutions to the short-term scheduling of a polymer plant involving multiple feasible solutions and parallel production lines. The DNA computer aided with nearest neighbour heuristics and iterative implementation found to be successfully searching the optimal solution in a combinatorial search space for three short-term scheduling problems of multi-grade polymer plant.
Published Version
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