Abstract: The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to dealwith the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the "excellent" infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the newalgorithm. Finally, the proposed algorithmis used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained.

Key words: Cracking furnace, Scheduling of feedstock, Group search optimizer, Adaptive penalty function, Double fitness values

摘要： The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to dealwith the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the "excellent" infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the newalgorithm. Finally, the proposed algorithmis used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained.

关键词: Cracking furnace, Scheduling of feedstock, Group search optimizer, Adaptive penalty function, Double fitness values