Articlehybrid2014

Multiobjective Optimization Model of Residential Spatial Distribution

Chengxiang Zhuge · Xiang Zhang · Jian Gao

6 citations0/0 files storedMathematical Problems in Engineering

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Transportation Planning and Optimization Facility Location and Emergency Management Advanced Multi-Objective Optimization Algorithms

Abstract

The concept of jobs‐housing balance has been adopted as an effective way to alleviate the traffic congestion, especially in metropolis. A multiobjective model of residential spatial distribution (MOOMRSD) is developed in this paper to address the problem of how to locate the housing in a reasonable way when the workplace location is given. Three objectives are integrated into the MOOMRSD and they are (1) minimizing the average commute cost from residence to workplace; (2) minimizing the total travel time of citizens; and (3) maximizing the aggregate utility and social benefit. In addition, a multiobjective genetic algorithm (MOGA) is proposed to figure out a satisfactory solution to the MOOMRSD. Finally, Both MOOMRSD and MOGA are applied into two cases.

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References

1990How to make a decision: The analytic hierarchy process 1988What is the Analytic Hierarchy Process?1989Jobs-Housing Balancing and Regional Mobility 1997The Jobs-Housing Balance and Urban Commuting 2008The jobs–housing relationship and commuting in Beijing, China: the legacy of Danwei 2009Impact of the jobs-housing balance on urban commuting in Beijing in the transformation era 2011Modeling the choice continuum: an integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions 1993The Changing Commute: A Case-study of the Jobs-Housing Relationship over Time

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2016Agent-based joint model of residential location choice and real estate price for land use and transport model 2015Joint Residence-Workplace Location Choice Model Based on Household Decision Behavior

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