ABSTRACT:The genetic algorithm technique is a relatively new optimization technique. In this paper we present a methodology for optimizing pipe networks using genetic algorithms. Unknown decision variables are coded as binary strings. We investigate a three-operator genetic algorithm comprising reproduction, crossover, and mutation. Results are compared with the techniques of complete enumeration and nonlinear programming. We apply the optimization techniques to a case study pipe network. The genetic algorithm technique finds the global optimum in relatively few evaluations compared to the size of the search space. INTRODUCTIONThe construction and maintenance of pipelines for water supply costs many millions of dollars every year. As funds for the development of new infrastructure become increasingly scarce, there is an increasing desire to achieve the highest level of effectiveness for each dollar spent. Traditionally, the design of water distribution networks has been based on experience. However, there is now a significant (and growing) body of literature devoted to optimization of pipe networks.
Abstract. An improved genetic algorithm (GA) formulation for pipe network optimization has been developed. The new GA uses variable power scaling of the fitness function. The exponent introduced into the fitness function is increased in magnitude as the GA computer run proceeds. In addition to the more commonly used bitwise mutation operator, an adjacency or creeping mutation operator is introduced. Finally, Gray codes rather than binary codes are used to represent the set of decision variables which make up the pipe network design. Results are presented comparing the performance of the traditional or simple GA formulation and the improved GA formulation for the New York City tunnels problem. The case study results indicate the improved GA performs significantly better than the simple GA. In addition, the improved GA performs better than previously used traditional optimization methods such as linear, dynamic, and nonlinear programming methods and an enumerative search method. The improved GA found a solution for the New York tunnels problem which is the lowest-cost feasible discrete size solution yet presented in the literature.
The decision to purchase a house is embedded within a set of economic and sociocultural processes and is operationalized within the context of a specific local property market. In the residential mobility literature considerable attention has been given to examining issues of house prices, life-course and demographic influences on the decision to buy, but less attention has been directed to understanding the internal family decision-making process. While the act of purchasing a property constitutes a significant economic event for a family, the process of purchasing a house is an inherently social activity, involving setting goals, discussing and negotiating family needs, interacting with exchange professionals (information intermediaries), imagining modifications to potential purchases and interpreting market trends. These family activities are shaped by family structures, gender roles, ethnicity and socio-economic status. In addition, the house purchase process takes place within specific market conditions and institutional practices. For example, in New Zealand, the estate agent has a large amount of power when negotiating contracts between buyers and sellers. Using in-depth interviews, this paper examines family decision processes in Auckland from the perspective of estate agents who deal with families purchasing houses on a daily basis, and formulate their own understanding of buyer behaviour, and adult family members who have recently purchased houses. The analysis makes it possible to explore the ways in which estate agents interpret the purchasing behaviour of families and to compare these interpretations with the understandings of adult family members. The study offers insights into the ways in which families engage in search practices, interpret information and internally negotiate decisions. It is argued that the findings here contribute a greater understanding of how housing markets are performed and made.
Increasingly, planning for housing development involves political conflict between local government planning practices, based on urban sustainability and housing intensification, and central government housing policies, centred on land supply and housing affordability. This paper examines a key historical moment in the politics of housing supply and planning in New Zealand. Drawing upon a discourse analysis of a range of housing policy documents and urban plans, this paper traces the dynamic of local and central government negotiations and conflict arising from the development of Auckland’s spatial plan, the development of the Auckland Housing Accord (a central and local government agreement to fast-track planning permission for new housing) and the implementation of the Housing Accords and Special Housing Areas Act. The paper focuses on the manner in which certain policy knowledge is prioritised and applied in the construction of affordable housing policies and how this process, which is presented as objective evidence-based policy formation, is inherently political. It is argued that the legislation supporting housing accords alters central/local government power relations and represents a challenge to the existing planning system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.