Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> In a bilevel decision problem, both the leader and the follower may have multiple objectives, and the coefficients involved in these objective functions or constraints may be described by some uncertain values. To express such a situation, a fuzzy multi-objective bilevel (FMOBL) programming model and related solution methods are introduced. This research develops a FMOBL decision support system through implementing the proposed FMOBL methods. <s> BIB001 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> In order to minimize the consumption of resources and the generation of waste, eco-industrial parks (EIPs) have been designed to encourage the establishment of waste exchange networks between the plants contained within them. Considering that the participating plants have their individual fuzzy cost goals and that the park authority has the objective of minimizing total freshwater consumption in the EIP, this problem may be formulated as a bi-level optimization problem, with the park authority as the upper-level decision-maker. A bi-level fuzzy optimization model is developed to explore the effect of charging fees for the purchase of freshwater and the treatment of wastewater in optimizing the water exchange network of plants in an EIP. The effect of subsidizing exchange of streams between plants is also included in the model. Results show that it is not necessary to impose exorbitant fees, nor to completely subsidize costs associated with recycling, in order to induce significant reduction of the consumption of freshwater in the EIP. <s> BIB002 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> Abstract In our previous paper, a fuzzy bi-level programming model was developed to determine optimal interplant water integration networks in eco-industrial parks (EIPs). This approach allowed the appropriate incentive mechanisms, in the form of fresh water and effluent fees as well as water reuse subsidies, to be optimized from the perspective of the EIP authority. This work extends the original mathematical model by modifying the role of the EIP authority to include water regeneration and redistribution via a centralized hub. The resulting fuzzy bi-level programming model may then be solved to yield a “satisficing” solution that reflects a reasonable compromise between the EIP authority's desire to minimize fresh water usage, and the participating companies’ desire to minimize costs. A case study is used to illustrate the modeling approach. <s> BIB003 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> This paper proposes a bilevel multiobjective optimization model with fuzzy coefficients ::: to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone plant so as to minimize total emissions and maximize employment and economic profit. On the lower level, stone plants must reasonably assign stone resources to produce different stone products under the exploitation constraint. To deal with inherent uncertainties, the object functions and constraints are defuzzified using a possibility measure. A fuzzy simulation-based improved simulated annealing algorithm (FS-ISA) is designed to search for the Pareto optimal solutions. Finally, a case study is presented to demonstrate the practicality and efficiency of the model. Results and a comparison analysis are presented to highlight the performance of the optimization method, which proves to be very efficient compared with other algorithms. <s> BIB004 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> AbstractThe allocation of water resources has long been recognized as a critical optimization problem. In this study, a bilevel programming model with fuzzy random variables is developed for tackling a regional water resources allocation problem on the basis of water rights distribution in a river basin. The bilevel programming model takes the optimal total benefit of the society and the optimal economic benefit of each subarea as the upper and lower targets, respectively. In contrast to previous studies, the balance of the satisfactory degree between the upper and lower decision makers is considered in the bilevel optimization for ensuring the equity of the water resource allocation. To deal with inherent uncertainties, the fuzzy random variables are first transformed into trapezoidal fuzzy numbers, and by taking advantage of the expected value operation, the trapezoidal fuzzy numbers are subsequently defuzzified. For solving the complex and nonlinear bilevel programming model, an interactive fuzzy progr... <s> BIB005 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> A bilevel optimization model for a hazardous materials transportation network design is presented which considers an emergency response teams location problem. On the upper level, the authority designs the transportation network to minimize total transportation risk. On the lower level, the carriers first choose their routes so that the total transportation cost is minimized. Then, the emergency response department locates their emergency service units so as to maximize the total weighted arc length covered. In contrast to prior studies, the uncertainty associated with transportation risk has been explicitly considered in the objective function of our mathematical model. Specifically, our research uses a complex fuzzy variable to model transportation risk. An improved artificial bee colony algorithm with priority-based encoding is also applied to search for the optimal solution to the bilevel model. Finally, the efficiency of the proposed model and algorithm is evaluated using a practical case and various computing attributes. <s> BIB006 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> This paper focuses on the problem of hedging against seismic risk through the retrofit of transportation systems in large-scale construction projects (LSCP). A fuzzy random multiobjective bilevel programming model is formulated with the objectives of the retrofit costs and the benefits on two separate levels. After establishing the model, a fuzzy random variable transformation approach and fuzzy variable approximation decomposition are used to deal with the uncertainty. An approximation decomposition-based multi-objective AGLNPSO is developed to solve the model. The results of a case study validate the efficiency of the proposed approach. <s> BIB007 </s> Fuzzy Bi-level Decision-Making Techniques: A Survey <s> Energy management and environment protection <s> AbstractTo optimize regional economies, social employment, and water quality protection, a multiobjective bilevel optimization model under a fuzzy random environment based on constructed wetland planning is developed in this study. Fuzzy random variables are used to describe the uncertainties in the system, and three special fuzzy random simulation methods are proposed to address the fuzzy random variable calculations. From the inherent bilevel model interaction, a new algorithm called the fuzzy random simulation-based nested genetic algorithm (FRS-based NGA) is designed as an intelligent solution to solve the model. Then, the model is applied to a real-world case: the Chaohu Lake watershed, China. The results under different objective values, probability levels, and possibility levels are compared so that an optimal scheme for regional economic development, social employment, and the wetland construction scale can be identified. Finally, the comparative analysis, sensitivity analysis, and convergence ana... <s> BIB008
Fuzzy bi-level decision-making techniques have been also applied to handle energy management problems in relation to the consumption of resources and the generation of waste. Aviso et al. [57] developed a fuzzy bi-level optimization model to explore the effect of charging fees for the purchase of freshwater and the treatment of wastewater in optimizing the water exchange network of plants in an eco-industrial park (EIP). Tan et al. BIB003 extended the optimization model developed by Aviso et al. BIB002 to a new fuzzy bi-level decision model by modifying the role of the EIP authority to include water regeneration and redistribution via a centralized hub, and found a reasonable compromise between the EIP authority's desire to minimize fresh water usage and the participating companies' desire to minimize costs. Xu et al. BIB005 developed a fuzzy random bi-level decision model for tackling a regional water resources allocation problem on the basis of water rights distribution in a river basin. The bi-level decision model targets to optimize the total benefit of the society and the economic benefit of each subarea respectively for the upper and lower levels. From the aspect of environment protection and risk analysis, Gan and Xu BIB007 considered a problem of hedging against seismic risk through the retrofit of transportation systems in large-scale construction projects (LSCP). They formulated this problem as a fuzzy random multi-objective bi-level decision model with the objectives of the retrofit costs and the benefits on two separate levels. Xu et al. BIB006 focused on a bilevel decision problem of hazmat transportation network design, which considers an location problem of emergency response teams. The authority at the upper level designs the transportation network to minimize the total transportation risk, while the carriers at the lower level choose their routes with the aim of minimizing the total transportation cost. The problem was formulated as fuzzy bi-level optimization model in which a complex fuzzy variable was used to model transportation risk, and then an improved artificial bee colony algorithm with priority-based encoding was applied to find an optimal solution to the resulting model. For the sake of optimizing regional economies, social employment, and water quality protection, Xu et al. BIB008 proposed a fuzzy random multi-objective bi-level optimization model for constructed wetland planning in which fuzzy random variables are used to describe uncertainties in the system. Yao et al. BIB004 gave a fuzzy bi-level multi-objective optimization model to handle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. A fuzzy simulation-based improved simulated annealing (FS-ISA) algorithm was developed to find the Pareto optimal solutions. In addition to these fuzzy bi-level decision-making applications in a range of domains, related decision support systems (software) have been developed to assist decision markers in solving fuzzy bi-level decision problems. Gao et al.  developed a fuzzy bilevel decision support system software based on fuzzy goal bi-level decision-making techniques, as shown in Fig. 1 , and applied the software to handle a problem of traffic management and risk analysis in a disaster area. The authors also applied the fuzzy bi-level decision support system to deal with a manufacturer-retailer decision problem in an uncertain marketing situation BIB001 . Fig. 1 . The main interface of the fuzzy bi-level decision support system developed by Gao et al.  BIB001 