DERIVING THE NONLINEAR RISK-BENEFIT ALGORITHM FOR RESERVOIRS1

ABSTRACT: The Nonlinear Risk-Benefit (NRB) Algorithm includes risk as one of the objectives in a multiple-objective optimization problem. The NRB Algorithm is derived by extending the Surrogate Worth Trade-Off method to quadratic programming. This category of problem is common in water resources planning and design, especially multipurpose reservoir systems. Consequently, an example is given using the algorithm for optimally operating a multipurpose reservoir.     

MULTICRITERIA PROGRAMMING OF WATER SUPPLY SYSTEMS FOR RURAL AREAS1

ABSTRACT: The aim of this paper is to present a multicriteria methodology for decision aid at the stage of programming a water supply system (WSS) for a rural area. The programming stage is an intermediate one between planning and designing water supply facilities, and can be decomposed into two problems: (a) setting up a priority order of water users, taking into account socio-economic criteria; and (b) choosing the best technical variant of the WSS. Among the criteria considered for the latter problem, there is a criterion of distance between the socio-economic priorities of users and the precedence orders of users according to the technical programming, which plays a coordinating role between problems (a) and (b). All steps of the presented methodology are illustrated by a real case study.     

MULTIOBJECTWE OPTIMIZATION OF RESERVOIR SYSTEMS OPERATION1

ABSTRACT: Development of optimal operational policies for large-scale reservoir systems is often complicated by a multiplicity of conflicting project uses and purposes. A wide range of multiobjective optimization methods are available for appraising tradeoffs between conificting objectives. The purpose of this study is to provide guidance as to those methods which are best suited to dealing with the challenging large-scale, nonlinear, dynamic, and stochastic characteristics of multireservoir system operations. As a case study, the selected methodologies are applied to the Han River Reservoir System in Korea for four principal project objectives: water supply and low flow augmentation; annual hydropower production, reliable energy generation, and minimization of risk of violating firm water supply requirements. Additional objectives such as flood control are also considered, but are imposed as fixed constraints.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

A MULTIOBJECTIVE MODEL FOR REGIONAL WATER QUALITY MANAGEMENT1

ABSTRACT: Linear programming is the simplest of all the optimization techniques used in regional water quality management studies; but the technique can optimize only one goal. When there are multiple goals with the same or different priorities, goal programming is a useful decisionmaking tool. This paper illustrates the application of goal programming to a regional water quality management problem where the following two goals are considered: (1) minimize the total cost of waste treatment, and (2) maintain the water quality goals (dissolved oxygen) close to the minimum level stated in the stream standards.     

Benefits of integrating complementarity into priority threat management

Conservation decision tools based on cost‐effectiveness analysis are used to assess threat management strategies for improving species persistence. These approaches rank alternative strategies by their benefit to cost ratio but may fail to identify the optimal sets of strategies to implement under limited budgets because they do not account for redundancies. We devised a multiobjective optimization approach in which the complementarity principle is applied to identify the sets of threat management strategies that protect the most species for any budget. We used our approach to prioritize threat management strategies for 53 species of conservation concern in the Pilbara, Australia. We followed a structured elicitation approach to collect information on the benefits and costs of implementing 17 different conservation strategies during a 3‐day workshop with 49 stakeholders and experts in the biodiversity, conservation, and management of the Pilbara. We compared the performance of our complementarity priority threat management approach with a current cost‐effectiveness ranking approach. A complementary set of 3 strategies: domestic herbivore management, fire management and research, and sanctuaries provided all species with >50% chance of persistence for $4.7 million/year over 20 years. Achieving the same result cost almost twice as much ($9.71 million/year) when strategies were selected by their cost‐effectiveness ranks alone. Our results show that complementarity of management benefits has the potential to double the impact of priority threat management approaches.     

Multiobjective optimisation method for life-cycle design of mechanical products

Manufacturing that minimises the exhaustion of natural resources, energy used and deleterious environmental impact is increasingly demanded by societies that seek to protect global environments as much as possible. To achieve this, life-cycle design (LCD) is an essential component of product design scenarios; however, LCD approaches have not been well integrated in optimal design methods that support quantitative decision-making. This study presents a method that yields quantitative solutions through optimisation analysis of a basic product design incorporating life-cycle considerations. We consider two types of optimisation approaches that have different aims, namely, (1) to reduce the use of raw materials and energy consumption and (2) to facilitate the reuse of the product or its parts when it reaches the end of its useful life. We also focus on how the optimisation results differ according to the approach used, from the viewpoint of the 3R concept (Reduce, Reuse and Recycling). Our method obtains optimum solutions by evaluating objectives fitted to each of these two optimisation approaches with respect to the product's life-cycle stages, which are manufacturing, use, maintenance, disposal, reuse and recycling. As an applied example, a simple linear robot model is presented, and Pareto optimum solutions are obtained for the multiobjective optimisation problem whose evaluated objectives are the operating accuracy of the robot and the different life-cycle costs for the two approaches. The characteristics of the evaluated objectives and design variables, as well as the effects of using material characteristics as design parameters, are also examined.     

Eco-efficiency in logistics: a case study on distribution network design

Sustainability demands that managers deliberate effects on stakeholders and the environment alongside traditional profitability measures. This paper presents a case study suggested by the managers of a distribution firm that seeks to balance environmental impact with cost in an industrial distribution network configuration decision incorporating product returns, which is currently taking place. While this can be modelled using mathematical programming, nonlinear terms in the objective functions as well as the likeliness that a large number of combinations of binary decision variables result suggest that this will not be able to be relied upon for a solution. For this reason, we propose a heuristic that aims at finding the Pareto-efficient frontier, which managers can use to deliberate the best solution balancing cost and environmental impact, according to the relative trade-offs of various possible configurations. We illustrate this heuristic on the Italian region of Liguria, and further explore trade-offs juxtaposing the regions of Lombardi and Sicily. Lastly, various extensions for enhanced product recovery opportunities for returns are suggested.     

污泥水磷和有机物同步混凝去除的多目标优化技术研究

通过引入多响应值的归一化评分法进行了污泥水磷和有机物同步混凝去除的多目标优化,并利用响应面(RSM)技术考察了Al/P比、聚丙烯酰胺(PAM)投加量和悬浮固体(SS)浓度对污染物去除的单独效应和联合效应.结果表明,复合投加聚合氯化铝和PAM能同步去除污泥水中磷和有机物,并改善沉降效果.归一化后单目标RSM优化显示,对污泥水中磷和有机物同步去除的贡献为Al/P比SS浓度PAM投加量.在最优条件Al/P比为3、PAM浓度为1.22 mg·L~(-1)、SS浓度为3.58 g·~(L-1)的条件下,正磷和总有机碳去除率分别为93.1%和53.9%.与多响应变量优化相比,引入归一化评分法有效解决了变量间数值量级差异的问题,使结果的分析计算变得简单方便.     

Rapidly assessing cobenefits to advance threat-management alliances

Conservation strategies aimed at reducing threats to biodiversity can have significant implications for multiple sectors in a socioeconomic system, but these cobenefits are often poorly understood. For example, many of the threats to native species also impede agricultural production, yet agriculture is typically perceived as in competition with conservation objectives. Although a comprehensive, multiobjective decision analysis is usually beyond the scope and capacity of conservation decision makers, failing to incorporate key socioeconomic costs and benefits into conservation decision-making processes can result in missed opportunities for diversifying outcomes and creating cost-sharing multisectoral partnerships. We devised a straightforward and readily interpretable approach to incorporate cobenefits into a threat-management prioritization approach. We used it to analyze the agricultural cobenefits of implementing 9 invasive animal management strategies designed to ensure the persistence of 148 threatened species across Australia's Lake Eyre Basin over 50 years. A structured elicitation process with 24 participants (scientists, land managers, agriculturalists, and other stakeholders) was used to collect information on each strategy, including costs, technical and social feasibility, benefits to native threatened species, and cobenefits to agricultural production systems. The costs of targeted invasive animal management to save threatened species across the basin (AU$33 million/year) outweighed the overall benefits to the agricultural industry (estimated AU$226 million/year). The return on investment for these management strategies varied substantially when agricultural cobenefits were considered alongside threatened species benefits and showed synergies and challenges. Our approach demonstrates the value of incorporating cobenefits of conservation actions into cost-effectiveness analyses to guide potential investment and partnerships and to diversify implementation pathways.