The problem of high water consumption and pollution emission of modern coal chemical industry have received widespread attention in recent years. However, while protecting the environment, the economic interests of coal chemical enterprises also need to be guaranteed. To address this challenge, this paper proposes an equilibrium strategy based on a bi-level multi-objectives model to assist decision-makers in coal chemical industrial parks in making plans for infrastructure investment, wastewater discharge load allocation, and production activities while balancing economic benefits, ecological protection, and energy efficiency promotion. The decision framework describes the hierarchical relationship between the park authority and individual coal chemical companies, and coordinates the conflicts between their different goals. Then, a real case study of Yushen coal chemical industrial park in Shaanxi province, China is presented using a hybrid algorithm named “particle swarm optimization - non-dominated sorting genetic algorithm - II (PSO-NSGA-II)” to solve multi-objectives programming. The research further discusses the final solutions under different preferences of decision-makers with the Subtractive clustering - Multi-criteria tournament decision - Gain analysis method (SC-MTD-GAM), and also compares the results of a single-objective optimization model and multi-objective programming. The results show that the equilibrium strategy of this research can provide a satisfactory consequence for coal chemical industrial parks in terms of integrative management involving the economy, environment and efficiency. Finally, based on a comprehensive discussion, management suggestions are given to help the related decision/policy-makers to develop sustainable management mechanisms.