Zhiqiu Gao

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization

Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision.

Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 2: improved extension theory

PurposeThe concept of sustainability and sustainable development has been widely incorporated in energy and industrial systems. This paper is the second part of a two-paper series dealing with multi-actor multi-criteria sustainability assessment of alternative energy and industrial systems in life cycle perspective under uncertainties.MethodsThe criteria system including four macroscopic aspects (environmental, safety, social and economic aspects) has been developed for sustainability assessment of energy and industrial systems. An improved extension theory which can address interval decision-making matrix has been developed for determining the sustainability degree of the energy and industrial systems.Results and discussionThe weights of the criteria for sustainability assessment are the first part of the two-paper series. An illustrative case has been studied by the proposed multi-criteria decision-making method, and the sustainability of six alternative options for the production of a 1-t product was investigated. The sustainability degree of these six alternative options can be determined by the proposed method.Conclusions and perspectivesA methodology for multi-actor multi-criteria sustainability assessment of energy and industrial options has been developed in this study, the traditional extension theory has been modified to deal with the uncertainty problems and the proposed method can rank the alternative energy and industrial systems with the decision-making matrix in which the data of the alternatives with respect to the evaluation criteria are intervals. In the improved extension theory, sustainability has been dived into five grades: excellent, good, satisfied, barely adequate and fail. According to the method for calculating the weights of the criteria for sustainability assessment proposed in part 1, these weights were used to calculate the integrated dependent degree which is a measure of what degree an alternative belongs to the classical fields. An optimal programming model for maximizing the satisfied degree has been developed to rank the sustainability sequence of the alternative options and determine the sustainability degree of each alternative.

Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 1: weighting method

PurposeLife cycle sustainability assessment is meaningful for the decision-makers/stakeholders to select the most sustainable option among multiple alternatives; however, there are usually various severe uncertainty problems in sustainability-oriented decision-making, i.e., the vagueness and ambiguity that existed in human judgments and the lack of information. This study aims at developing a novel life cycle multi-criteria sustainability assessment method for helping the decision-makers/stakeholders to determine the sustainability level of the industrial and energy systems. In part 1, an improved interval analytic hierarchy process (AHP) which allows multiple decision-makers/stakeholders to participate in the decision-making was developed to determine the weights of the criteria which were used in life cycle sustainability assessment.MethodsIt is usually difficult for the decision-makers/stakeholders to use the numbers from 1 to 9 and their reciprocals for determining the comparison matrix when using the traditional AHP method for weight calculation, because human judgments usually involve various uncertainties. In order to the overcome this weak point of the traditional AHP, an improved AHP, so-called interval AHP, in which, multiple decision-makers/stakeholders are allowed to participate in the decision-making and allowed to use interval numbers instead of crisp numbers to establish the comparison matrix for determining the weights of the criteria for life cycle sustainability assessment, has been developed.Results and discussionThe proposed method was used to determine the weights of the four aspects for life cycle sustainability assessment including economic, safety, social, and environmental aspects. Five representative stakeholders were invited to participate in the decision-making. After Monte Carlo simulation, the final weights of the four aspects have been determined with the proposed interval AHP.Conclusions and perspectivesAn interval AHP method was developed for determining the weights of the criteria for life cycle sustainability assessment; the decision-makers are allowed to use interval numbers to establish the comparison matrix for weight calculation. The weighting coefficients determined by Monte Carlo method can accurately reflect the preferences and willingness of multi-actor comparing with the traditional AHP method. This paper merely presents a novel method to calculate the weights of the criteria for life cycle sustainability assessment, but the method for determining the sustainability performance has been presented in part 2.

Comparison of Different Multicriteria Decision-Making Methodologies for Sustainability Decision Making

The objective of this chapter is to compare different weighting methodologies and different multicriteria decision-making methodologies for sustainability decision making. Four weighting methodologies and four multicriteria decision-making methodologies have been compared in this chapter; the weighting methodologies comprise two objective methodologies (entropy method and ideal point method) and two subjective methodologies (analytic hierarchy process and Delphi method), the multicriteria decision-making methodologies consist of four options, including technique for order of preference by similarity to ideal solution, data envelopment analysis, preference ranking organization method for enrichment evaluation, and principal component analysis. The proposed weighting methodologies and multicriteria decision-making methodologies have been compared by applying them on sustainability decision making among five energy scenarios.