Y.P. Cai

An optimization-model-based interactive decision support system for regional energy management systems planning under uncertainty

In this study, an interactive decision support system (UREM-IDSS) has been developed based on an inexact optimization model (UREM, University of Regina Energy Model) to aid decision makers in planning energy management systems. Optimization modeling, scenario development, user interaction, policy analysis and visual display are seamlessly integrated into the UREM-IDSS. Uncertainties in energy-related parameters are effectively addressed through the interval linear programming (ILP) approach, improving the robustness of the UREM-IDSS for real-world applications. Thus, it can be used as an efficient tool for analyzing and visualizing impacts of energy and environmental policies, regional/community sustainable development strategies, emission reduction measures and climate change in an interactive, flexible and dynamic context. The Region of Waterloo has been selected to demonstrate the applicability and capability of the UREM-IDSS. A variety of scenarios (including a reference case) have been identified based on different energy management policies and sustainable development strategies for in-depth analysis of interactions existing among energy, socio-economy, and environment in the Region. Useful solutions for the planning of energy management systems have been generated, reflecting complex tradeoffs among energy-related, environmental and economic considerations. Results indicate that the UREM-IDSS can be successfully used for evaluating and analyzing not only the effects of an individual policy scenario, but also the variations between different scenarios compared with a reference case. Also, the UREM-IDSS can help tackle dynamic and interactive characteristics of the energy management system in the Region of Waterloo, and can address issues concerning cost-effective allocation of energy resources and services. Thus, it can be used by decision makers as an effective technique in examining and visualizing impacts of energy and environmental policies, regional/community development strategies, emission reduction measures, and climate change within an integrated and dynamic framework.

Investigation of public's perception towards rural sustainable development based on a two-level expert system

Sustainable development is of great significance in rural areas of China, which are under coupled pressures of poverty reduction, environmental protection and economic development. In these areas, agriculture is the primary sector in supporting their economies, where a number of the relevant production and processing practices cause many adverse impacts on environment and ecosystem. This poses many challenges for decision makers in formulating sustainable development strategies without invoking potential controversies or objections from the public. In this study, a two-level expert system (TES) for facilitating the investigation of publics perception towards sustainable development in rural areas was developed. Interactive relationships among objectives of socio-economic development and environmental protection, as well as the related policy implications and public responses, were comprehensively examined and incorporated within TES. A two-level system was particularly adopted for facilitating participation of various stakeholders, including decision makers and farmers. The Yongxin County of the Shanjianghu Region in Jiangxi Province, China was selected to demonstrate the applicability of the developed TES. A series of questionnaire surveys were conducted both for acquiring knowledge about the interrelationships among sustainable development, agricultural production, poverty reduction and environmental protection. Publics perception towards various system components of rural sustainable development were efficiently acquired and analyzed. The results indicated that sustainable development would be very significant on rural areas in China. Also, public awareness to the concept and profile of rural sustainable development was still at a low level, especially for farmers. The developed TES can be not only used for acquiring knowledge of sustainable development, but also providing basic information for the formulation of relevant policies and strategies in rural areas of China.

Multi-Source Multi-Sector Sustainable Water Supply Under Multiple Uncertainties: An Inexact Fuzzy-Stochastic Quadratic Programming Approach

This paper presents the development and the first application of a superiority–inferiority-based inexact fuzzy-stochastic quadratic programming (SI-IFSQP) approach for sustainable water supply under multiple uncertainties. SI-IFSQP improves conventional nonlinear programming by tackling multiple uncertainties within an individual parameter; SI-IFSQP is also superior to existing inexact methods due to its reflection of economies of scale and reduction of computational requirements. An interactive solution algorithm with high computational efficiency was also proposed. The application of SI-IFSQP to long-term planning of a multi-source multi-sector water supply system demonstrated its applicability. The close reflection of system complexities, such as multiple uncertainties, scale economies and dynamic parameters, could enhance the robustness of the optimization process as well as the acceptability of obtained results. Corresponding to varied system conditions and decision priorities, the interval solutions from SI-IFSQP could help generate a series of long-term water supply strategies under a number of economic, environmental, ecological, and water-security targets.

A Generalized Interval Fuzzy Chance-Constrained Programming Method for Domestic Wastewater Management Under Uncertainty – A Case Study of Kunming, China

In this study, interval mathematical programming (IMP), mλ-measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to a generalized interval fuzzy chance-constrained programming (GIFCP) method. GIFCP can be used to address not only interval uncertainties in the objective function, variables and left-hand side parameters but also fuzzy uncertainties on the right-hand side. Also, it can reflect the aspiration preference of optimistic and pessimistic decision makers due to the integration of mλ-measure. The developed method is applied to the long-term planning of a domestic wastewater management system in the city of Kunming, China, with consideration of the eco-environmental protection of downstream water body. The solution results of the GIFCP method can generate a series of optimal wastewater allocation patterns and WTPs capacity expansion schemes under different risk levels, provide in-depth insights into the effects of uncertainties, and consider the proper balance between system cost and risk of constraint violation.

An interval-parameter mean-CVaR two-stage stochastic programming approach for waste management under uncertainty

In this research, approaches of interval mathematical programming, two-stage stochastic programming and conditional value-at-risk (CVaR) are incorporated within a general modeling framework, leading to an interval-parameter mean-CVaR two-stage stochastic programming (IMTSP). The developed method has several advantages: (i) it can be used to deal with uncertainties presented as interval numbers and probability distributions, (ii) its objective function simultaneously takes expected cost and system risk into consideration, thus, it is useful for helping decision makers analyze the trade-offs between cost and risk, and (iii) it can be used for supporting quantitatively evaluating the right tail of distributions of waste generation rate, which can better quantify the system risk. The IMTSP model is applied to the long-term planning of municipal solid waste management system in the City of Regina, Canada. The results indicate that IMTSP performs better in its capability of generating a series of waste management patterns under different risk-aversion levels, and also providing supports for decision makers in identifying desired waste flow strategies, considering balance between system economy and environmental quality.

An inexact optimization model for evacuation planning

Purpose – The purpose of this paper is to develop an interval method for vehicle allocation and route planning in case of an evacuation.Design/methodology/approach – First, the evacuation route planning system is described and the notations are defined. An inexact programming model is proposed. The goal of the model is to achieve optimal planning of vehicles allocation with a minimized system time under the condition of inexact information. The constraints of the model include four types: number of vehicles constraint, passengers balance constraints, maximum capacity of links constraints and no negative constraints. The model is solved through the decomposition of the inexact model. A hypothetical case is developed to illustrate the proposed model.Findings – The paper finds that the interval solutions are feasible and stable for evacuation model in the given decision space, and this may reduce the negative effects of uncertainty, thereby improving evacuation managers estimates under different conditions....

Identification of Strategies for Adaptation Planning to Extreme Events under Climate Change

Global climate change has significant but uncertain impacts on hydrological regimes as well as flooding patterns of a watershed, which may probably result in the enlargement of flood-prone areas and the loss of life and property. It is desired to develop effective approaches to identify optimal strategies of flooding adaptation under changing climatic conditions. In this study, a mixed integer fuzzy interval-stochastic programming (MIFISP) method is proposed for the planning of flood-retention capacity in flood-prone areas of a watershed based on the existing methods of interval linear programming (ILP), two-stage programming (TSP) and fuzzy linear programming (FLP). The developed MIFISP model is then applied to a typical watershed in western Canada. The results indicate that MIFISP can be employed for quantitatively analyzing flood- retention capacity management policies in the flood plain that are associated with different levels of economic penalties when the promised policy targets are violated. It is also implied that the model is effective for the identification of adaptation strategies to various flood events under changing climatic conditions.