THE DEVELOPMENT OF A PLAN OF STUDY – AN INTERAGENCY APPROACH TO MULTIOBJECTIVE PLANNING AND EVALUATION OF WATER AND LAND RESOURCE USE1

ABSTRACT The paper presents a systems approach for planning and evaluating alternative plans for resource use incorporating the concepts of multiobjective planning and evaluation (MOPE). The need for multidisciplinary input and strong interagency cooperation in planning for resource use is related to the logical and orderly completion of the planning steps. The paper briefly describes MOPE, emphasizing two important concepts: (1) the relationship of the study problems and objectives to national social objectives, and (2) the display of alternative solutions showing tradeoffs. Several important characteristics of a plan of study which implements MOPE are presented and discussed. A proposed MOPE analytical system is discussed in detail. The MOPE analytical system is divided into eight interdependent subsystems that describe data collection, use, analysis, and results. A linear program (L.P.) model is proposed to analyze the present and future demand relationships for natural resources. The model will also evaluate the interaction of agriculture, forestry, and recreation with the resource base of the basin, considering National Economic Development, Environmental Quality, and Regional Development.     

THE CENTRAL ARIZONA WATER CONTROL STUDY: A CASE FOR MULTIOBJECTIVE PLANNING AND PUBLIC INVOLVEMENT1

This paper describes the successful application of a multiobjective planning framework, incorporating substantial public involvement, to a major water resources decision involving intense confilcts. The study was initiated to help resolve more than a decade of controversy over a project proposed to control flooding and provide regulatory storage in the Phoenix, Arizona, area. The public was actively involved in the development of study goals and the specification of acceptable tradeoffs between multiple objectives. A wide range of structural and nonstructural alternatives was formulated and evaluated in relation to these objectives, and broad-based support was developed for a new plan. Reasons for the successful outcome are discussed, as well as implications for water resources planning under the new Federal Principles and Guidelines.     

Mathematical Methods for Spatially Cohesive Reserve Design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.     

Genetic algorithm optimisation of water consumption and wastewater network topology

Genetic algorithm (GA) optimisation applied to water systems with multiple contaminants and several contaminated sources is presented. This approach generates the overall optimal water network topology with respect to the minimum supply water usage, complying, in the same time, with all restrictions. An optimal water network could be viewed as an oriented graph, starting from unit operations which must not have contaminants at entrance (inlet contaminants-free unit operations), every next unit operation i receiving streams from the previous operations j only (j = 1, 2,…,i−1), and sending streams to the next operations j (j = i + 1, i + 2,…,N). The mathematical model describing the unit i is based upon total and contaminant species’ mass balances, together with the input and output constraints. Solving this optimisation problem is not trivial, since the unknowns' number, determines the number of equations. The GA optimisation uses each network's internal flow as a gene, assembling the topology into a chromosome. The restrictions, in terms of minimum and maximum allowable flows for each gene, are dealt with naturally, during the population generation, simply rejecting those genes outside their feasible domain. The individuals are interbred according to their frequency of selection, using the one-point crossover method, and then mutations are applied to randomly selected individuals. The objective function is the total supply water consumption, which should be minimised.     

Life cycle optimisation (LCO) of product systems with consideration of occupational fatalities

With the increasing pressures imposed upon industries on the environmental impacts of the manufacturing industry and chemical processes, numerous methodologies have been developed for the quantification, assessment and minimisation of waste and emissions. Meanwhile, methods for the simultaneous maximisation of economic performance within a product life cycle have also been developed. Similarly, various methodologies for screening of process alternatives based on the above factors have also been developed. However, the human lives put at risk in a supply chain constituting a life cycle tend to be overlooked as a factor of assessment, selection and optimisation of the process. Despite having life cycle assessment (LCA) methodologies for environmental assessment, no methodology has been developed for the minimisation of work-related casualties due to the unpredictable nature of workplace accidents. To address this problem, this paper develops a multi-objective optimisation model that utilises realistic statistical data for estimating the best possible pathway. The model results in the least potential fatality directly involved within the product life cycle while simultaneously minimising operating costs throughout the entire life cycle. A case study involving the utilisation of palm-based biomass formed for the production of value-added green products in Malaysia is used to demonstrate the model.     

Evolution,variability and sustainable development

SUMMARY

Sustainable development is a global challenge to science and society. In politics and economics the concepts for establishing a sustainable society are numerous, nonetheless necessary interdisciplinary approaches are still marginalised. Trying to foster a deeper communication between biology and social science, an evolutionary perspective on sustainable development is offered. Subsequently, the role of variability and diversity in evolution is highlighted. Hereby, special attention is devoted, among other things, to the links between variability and stability in the long term. Next, selection and variability are emphasised in the cultural context. This is followed by general implications for sustainability. In contrast to strategies aiming at short-term optimisation and economic efficiency, we argue that the conditions and circumstances maintaining variability and momentary sub-optimal alternatives are highly relevant for a socio-economic system that is heading for sustainable development.     

连续流分段进水工艺生物脱氮除磷技术分析及优化控制

连续流分段进水工艺可最大程度利用污水碳源,对低C/N城镇生活污水及工业废水具有深度脱氮除磷特性.详述了连续流分段进水工艺生物脱氮除磷原理和工艺特性,重点分析了段数、流量分配比、各段缺氧区和好氧区容积分配比、溶解氧、污泥回流比、原水水质等对工艺运行性能的影响因素.并结合国内外研究现状和工程应用实例,概述了工艺的过程控制的研究情况和应用前景.开展针对中国污水水质的工艺设计试验研究和相应的工艺过程控制研究是加快分段进水工艺应用于中国污水处理行业的两大技术突破点.     

Construction of an optimum system design method considering product lifecycle

This paper proposes an optimum system design method that especially considers product lifecycles and aims to help designers make effective decisions during the product design phase. By considering and estimating all lifecycle factors of cost and environmental impact in addition to the product performance, this method facilitates development of optimum design solutions that incorporate requirements pertaining to the product's entire lifecycle. Furthermore, quantitative estimation of lifecycle factors enables the numerical expression of optimum solutions, rather than depending primarily on experiment and designer intuition. To demonstrate the effectiveness of the proposed method, this paper develops an optimum system design method for a milling machine as an example of a machine product designed for long term use. The lifecycle cost and the lifecycle environmental impact are generally expressed as the summation of each value during manufacturing phase, usage phase, disposal phase and recycling phase. In this example model, Eco-indicator 99 is used to evaluate environmental impact. In the proposed lifecycle design optimisation method, the relationships among the product performance, the lifecycle cost and the lifecycle environmental impact are evaluated as a multi-objective optimisation problem. Analysis of the obtained Pareto optimum solution sets subsequently enables designers to pursue breakthrough product design solutions.     

Sustainable supply chain network design: a multicriteria perspective

In this paper, we develop a rigorous modelling and analytical framework for the design of sustainable supply chain networks. We consider a firm that is engaged in determining the capacities of its various supply chain activities, i.e. the manufacturing, storage and distribution of the product to the demand locations. The firm is faced with both capital costs associated with constructing the link capacities and the links' operational costs. Moreover, the firm is aware of the emissions generated associated with the alternative manufacturing plants, storage facilities and modes of transportation/shipment, which may have different levels of emissions due, for example, to distinct technologies of, respectively, production, storage and transportation. The firm is assumed to be a multicriteria decision-maker who seeks to not only minimise the total costs associated with design/construction and operation, but also to minimise the emissions generated, with an appropriate weight, which reflects the price of the emissions, associated with the various supply chain network activities. We provide both the network optimisation modelling framework and an algorithm, which is then applied to compute solutions to a spectrum of numerical sustainable supply chain design examples in order to illustrate our approach.