## 2 Literature Review  
Compared to the energy conservation and emission reduction system within a single industry, the system based on the polygeneration process is more complex and uncertain [17; 18; 19]. As a result, many studies have focused on the simulation and performance evaluation of polygeneration systems. Among them, techno-economic evaluation is a typical evaluation criterion since the economic effect is the primary motivation to build the system. For example, [PERSON] et al. [20] and [PERSON] et al. [21] had conducted techno-economic evaluation in a polygeneration system from coke oven gas and steel-mill off-gases, while similar evaluations can be seen in the system based on the LNG-regasification [22; 23], catalytic hydroprolysis [24], and agricultural residue [25]. In addition, energy efficiency is widely regarded as a vital evaluation indicator, especially in the polygeneration system of energy [26; 27]. [PERSON] et al. [28] have compared a custom coal-fired power plant with air-blown IGCC polygeneration ones and found that there is a 6% increase in energy efficiency after adopting the polygeneration system. [PERSON] et al. [29] have taken three Spanish cities as examples to investigate the energy performance of the power-heat polygeneration plant in different ways. Environmental indicators have been considered in studies via a series of methods such as emission coefficient [30], life-cycle assessment [31; 32; 33], and environmental cost analysis [34]. These methods have proved the advantages of polygeneration systems via different evaluation criteria. However, since the evaluation could only be conducted among limited scenarios, these studies have usually focused on the current status of the system and thus cannot support the decision-makers to select the technologies in the polygeneration system and choose the optimal schemes. To overcome this shortcoming, many studies have focused on the optimization and design of the polygeneration and have adopted multiple optimal methods. Among them, mixed-integer programming is a common model, usually taking best economic performance as the objective. [PERSON] et al. (2018) have built a mixed-integer nonlinear programming model to search for an optimal economic profit in an electricity-methanol polygeneration plant. [PERSON] (2018) has summarized the advantages and limitations of mixed-integer nonlinear programming in solving the problems of polygeneration system designs. Other research has also adopted this method to optimize biomass co-generating technology selection ([PERSON] et al., 2019), the selection of the contracted power from the grid within different renewable sources ([PERSON] et al., 2019), and the building of microgrid polygeneration systems ([PERSON] et al., 2019). Though these studies have supported the improvement of polygeneration systems, they have solved single objective optimization problems and neglected other energy and environmental objectives as well as the trade-off relationship between them. In this situation, the optimal results they have obtained may have biases from the comprehensive optimal ones. Some other studies have avoided this problem and have considered two or more objectives simultaneously. [PERSON] and [PERSON] et al. (2019) have investigated the optimal material and energy flows in a biomass polygeneration system under maximum exergy efficiency and minimum cost. [PERSON] et al. (2019) have focused on the forest industry and designed a bi-objective model to seek for the lowest economic cost and highest ecological effects. These studies have transferred multi-objectives into single ones through different methods, such as the monetary and weighted sum method, with the relationship between objectives subjectively defined. Another type of multi-objective solution method is the searching algorithm, which also has wide applications. For example, both [PERSON] et al. (2019) and [PERSON] et al. (2019) have adopted evolutionary algorithms in energy polygeneration system designs by combining energy, exergy, and economic objectives.