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The purpose of this paper is to propose a cradle-to-cradle (C2C) zero discharge production planning system with a fuzzy hybrid optimization model that uses fuzzy comprehensive evaluation to establish fuzzy indicators, and then defuzzify the fuzzy indicators to construct a fuzzy multiobjective programming (FMOP) model.

The FMOP model pursues overall satisfaction using a particle swarm optimization algorithm to produce the best output values for the maximum waste paper recovery rate, the condensate reuse quality and minimum total cost of the zero discharge production planning system.

Recovered waste heat is seldom recycled and consumed in Taiwan. There is a need to capture and utilize heat recovery and use it in the production process supply. In contrast, waste materials are used as resources to perform waste paper recovery and recycle the waste heat of evaporation collection in the production process.

This paper develops a system to establish the best output value for an overall high satisfaction level. According to the results, the waste paper recovery rate is 99.8 percent, condensate reuse quality water is 102.6 tons and the total cost of the zero discharge production planning system is NT$1,312,012.

The purpose of this paper is to analyze the wastewater discharge and a zero-wastewater-discharge (ZWD) reproduction plan is designed for a paper mill in Taiwan.

The proposed model of ZWD reproduction planning is established using the fuzzy comprehensive evaluation and Taguchi method to determine the overall wastewater recovery rate. Still the prior studies failed to address a systematic approach to optimize the waste water recovery rate.

The optimal solution for clean water is 500 tons, recovery electrodialysis reversal is 345 tons, the wastewater reuse performance is 1.3 and waste heat recycling performance is 0.8, the larger number is performed well. The results shows that the maximum overall waste water recovery rate is 97.8 percent.

A paper mill is strived for improving their sustainable development. In real situation, there is a need to address the qualitative information and qualitative data to carry out the optimal ZWD reproduction planning.

The purpose of this paper is to develop an integrated approach for a green product cradle-to-cradle (C2C) fuzzy recycling production planning model.

This paper applies the failure mode and effects analysis technique and Taguchi experimental design method, develops a green product C2C performance evaluation system that considers the fuzzy impacts of environmental laws and regulations, green goodwill, and environmental efficiency of targeting countries, and decides both the optimal green production plan and estimated optimal life cycles.

This study compares the different degree of maturity in environmental regulations, and various recycling situations are simulated to demonstrate the successful applicability of the proposed model as well as the incentive policy for Taiwan, the USA and Bangladesh.

Previous studies failed both to develop a holistic recycling production plan which is able to consider both the optimal combination of recycled components used and final green products produced with the maximum total resultant sales profit and to consider the potential failure phenomenon of recycled components adopted in the final product. Furthermore, most prior studies ignored the influence of environmental law, goodwill of the product and the efficiency of recycling mechanism of the community.

Construction and demolition waste (CDW) continuously causes environmental and social problems. These formidable challenges lead to sustainable issues and are an increasingly urgent issue worldwide. Prior studies have neglected to link the triple bottom line (TBL) to a reliable estimation or empirical model for estimating CDW production performance and lack empirical sensitivity analysis in profit maximization. This study proposes an attribute analysis to build a cost–benefit analysis (CBA) to obtain profit maximization.

This study uses fuzzy set theory to develop a cost and benefit analysis (CBA) model to assess the sensitivity analysis in terms of its performance on addressing the environmental, economic and social aspects. The model is used to weigh the sum of benefits such as financial gain and total costs of actions taken to mitigate the negative impacts.

Based on the sensitivity analysis conducted, the environmental, economic and social mean scales were significantly changed, i.e. increased, and profits increased drastically. The results provide an insight into environmental legislation compliance, environmental investment and environmental impact as the cause attributes for the CDW recycling profit increase. The results prove that sensitivity analysis is viable to infer that a sustainable production performance can achieve more revenue and profit through an adequate selection of attributes regarding the TBL aspects to address the firm's uncertainty problem in multiple criteria analysis.

This study builds a CBA model to maximize profits for recycled CDW material by linking of environmental, economic and societal aspects for recycled CDW assessments. It considers a sustainability structure with criteria based on TBL aspects to assess production performance to realize the Sustainable Development Goals and presents fuzzy set theory and sensitivity analysis to solve the uncertainty problem in the construction industry.

This study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm.

The objectives of this study are to (1) identify the environmental, technical and social metrics in resource efficiency; (2) utilize fuzzy multi-objective programming and the hybrid particle swarm optimization algorithm to solve the fuzzy problem; and (3) develop an assessment for resource efficiency improvement in an industrial case study.

The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.

The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.

Resource efficiency is a multi-objective problem in an uncertain environment. In particular, zero waste discharge planning involves minimizing the total cost and maximizing the waste material recovery rate, wastewater reuse, and waste heat recovery.