The industrial energy recovery network has a large energy-saving potential. The retrofit of the original heat exchanger network (HEN) plays an important role in reducing energy consumption in existing process industries. However, a single economic or energy target is no longer sufficient to meet the retrofit needs of existing process industries. Therefore, an improved retrofit method that comprehensively considers many-objective is worthy of exploration. In this study, a many-objective optimization model with energy, economic, environmental and engineering quantity (4E) indexes for heat exchanger network retrofit is proposed, which avoids the one-sided analysis brought by single-objective optimization. The non-dominated sorting genetic algorithm based on reference point (NSGA-III) is applied to solve the proposed retrofit model. Three typical cases are used to verify and analyze the effectiveness and superiority of the proposed method. The case results show that the many-objective optimization method provides diverse retrofit options and flexibility to decision makers. Retrofit schemes with comparative energy, economic or environmental performance may take on notable difference in engineering quantity. Compared with the original networks, the retrofitted networks in the case studies can achieve a decrease in energy consumption up to 49.6%, a decrease in the total annual cost up to 22.2%, and a decrease in environmental impact up to 32.8%. Compared with the literature, the proposed method obtains optimization solutions with less energy consumption, capital cost, environmental impact and payback period.

工业能源回收网络具有很大的节能潜力。原始热交换器网络（HEN）的改造在降低现有过程工业的能耗方面起着重要作用。但是，单一的经济或能源目标已不足以满足现有加工行业的改造需求。因此，一种综合考虑多目标的改进改造方法值得探索。本研究提出了一种具有能源，经济，环境和工程量（4E）指标的多目标优化模型，用于换热器网络改造，避免了单目标优化带来的单方面分析。应用基于参考点的非支配排序遗传算法（NSGA-III）来求解所提出的改进模型。通过三个典型案例验证和分析了该方法的有效性和优越性。案例结果表明，多目标优化方法为决策者提供了多种改造选项和灵活性。具有可比的能源，经济或环境绩效的改造方案可能在工程数量上有显着差异。与原始网络相比，案例研究中的改造网络可以减少多达49.6％的能耗，减少年度总成本的22.2％，减少对环境的影响的32.8％。与文献相比，该方法获得了能耗，资金成本，环境影响和投资回收期更少的优化解决方案。