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The aim of this study was to determine the number of shelters, specify some optimal paths among building blocks towards shelters, and assign population to shelters.

Imperialist competition algorithm (ICA) and particle swarm optimization (PSO) were used to optimize the objectives of this study.

The optimal value for PSO objective function was with the number of function evaluations (NFE) of 5300 and the optimal value of ICA objective function was with NFE of 1062. Repetition test for both algorithms showed that imperialist competition algorithm enjoys better stability and constancy and higher speed of convergence compared to particle swarm algorithm. This has been also shown in larger environments. 92% of the existing populations have access to shelters at a distance of less than600 meters. This means that evacuation from the building blocks to shelters takes less than 8 minutes. The average distance from a block (for example, a residential complex) to an optimal shelter is approximately273meters. The greatest risk of route and shelter has been 239 and 121, respectively.

To address these goals, four following objective functions were considered: a) minimization of the distance for getting all the people to shelters b) the lowest total risk of the discharge path c) minimization of the total time required to transfer people to shelters or hospitals if necessary, and d) the lowest total risk in shelters.

Over the recent decades, the frequency of so-called ‘natural’ disasters has increased significantly worldwide and resulted in escalating human and economic losses. Among them, the earthquake is one of the major concerns of the various stakeholders related to urban planning.

In addition, the maximum time of discharge from the helter to the hospital has been 17 minutes, which means the presence of good access to selected shelters.

This paper aims to investigate the effectiveness of early warning and community cooperation for evacuation preparedness from mega-risk type coastal hazard in childcare centers, focusing in the evacuation of childcare centers from tsunami at the time of the Great East Japan Earthquake occurred on March 11, 2011.

As the research method, surveys were conducted in public childcare centers affected by tsunami in Kesennuma city in Miyagi Prefecture and Kamaishi city in Iwate Prefecture.

As the main findings, facilities, where teachers and children started evacuation immediately after the earthquake, could have more conditions to get cooperation from the local community to evacuate children in wide-scale urban environment. Children 3-5 years old tended to be instructed to walk two abreast under the lead of teachers, and children 0-2 years old tended to be carried by the piggyback ride and multi-passenger baby strollers. The destination of evacuation needed to be changed several times because of the risks for higher tsunami and fire outbreaks.

As future issues, it is necessary to analyze the walking capability of children and the transportation capability of multi-passenger baby strollers by teachers, to address strategies to quantify the necessary community cooperation based on the severity of early warning.

Most of the past studies regarding disaster preparedness of nursery children are limited within the facility in case of fire. This work has importance as it focused on the emergency responses that require urban-scale evacuation in ascending route that differ from that which are required in the case of fire.

The purpose of this paper is to formulate and solve a new emergency evacuation planning problem. This problem addresses the needs of both able and disabled persons who are evacuated from multiple pick-up locations and transported using a heterogeneous fleet of vehicles.

The problem is formulated using a mixed integer linear programming model and solved using a heuristic algorithm. The authors analyze the selected heuristic with respect to key parameters and use it to address theoretical and practical case studies.

Evacuating people with disabilities has a significant impact on total evacuation time, due to increased loading/unloading times. Additionally, increasing the number of large capacity vehicles adapted to transport individuals with disabilities benefits total evacuation time.

The mathematical model is of high complexity and it is not possible to obtain exact solutions in reasonable computational times. The efficiency of the heuristic has not been analyzed with respect to optimality.

Solving the problem by a heuristic provides a fast solution, a requirement in emergency evacuation cases, especially when the state of the theater of the emergency changes dynamically. The parametric analysis of the heuristic provides valuable insights in improving an emergency evacuation system.

Efficient population evacuation studied in this work may save lives. This is especially critical for disabled evacuees, the evacuation of whom requires longer operational times.

The authors consider a population that comprises able and disabled individuals, the latter with varying degrees of disability. The authors also consider a heterogeneous fleet of vehicles, which perform multiple trips during the evacuation process.

Urban communities can be faced with many destructive events that can disrupt the daily functioning of activities and livelihood of people living in the communities. In this regard, during the last couple of years, many governments have put a lot of efforts into building resilient urban communities. Essentially, a resilient urban community has the capacity to anticipate future disasters, prepare for and recover timely from adverse effects of disasters and unexpected circumstances. Considering this, it is therefore important for the need to continuously review the existing urban community resilience indicators, in order to identify emerging ones to enable comprehensive evaluation of urban communities in the future against unexpected events. This study therefore aims to conduct a systematic review to develop and critically analyse the emerging and leading urban community resilience indicators.

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRSIMA) protocol, 53 journal articles were selected using Scopus. The selected papers were subjected to thorough content analysis.

From the review, 45 urban community resilience indicators were identified. These indicators were grouped into eight broad categories namely, Socio-demographic, Economic, Institutional Resilience, Infrastructure and Housing Resilience, Collaboration, Community Capital, Risk Data Accumulation and Geographical and Spatial characteristics of community. Further, the results indicated that the U.S had the highest number of publications, followed by Australia, China, New Zealand and Taiwan. In fact, very few studies emanated from developing economies.

The outputs of this study will inform policymakers, practitioners and researchers on the new and emerging indicators that should be considered when evaluating the resilience level of urban communities. The findings will also serve as a theoretical foundation for further detailed empirical investigation.

This paper aims to study a dynamic post-disaster emergency planning (PDEP) problem in an integrated network through the investigation of the selection of shelters, medical centers and distribution centers (DCs), and the allocation of evacuees and injured people. The resource and people assignment in multiple periods are considered.

A mathematical formulation is provided for the PDEP problem. The authors decompose the model into two sub-models as follows: the primary model is an integer programming model and the subproblem is a nonlinear programming model with continuous variables. The simulated annealing is used to solve the primary problem, and particle swarm optimization (PSO) mixed with beetle antennae search (BAS) is used to solve the subproblem.

The paper finds that BAS can increase the stability of PSO and keep the advantages of PSO’s rapid convergence. By implementing these algorithms on emergency planning after the Wenchuan earthquake that happened in China in 2008, this paper finds that the priority of different levels of injured people is influenced by several factors. Even within the same disaster, the priority of different levels of injured can be inconsistent because of the differences in resource levels.

The authors integrate the shelters, medical centers and DCs as a system, and simultaneously, consider evacuees and injured people and different resource assignments. The authors divide the injured people into three levels and use survival rate function to simulate the survival conditions of different people. The authors provide an improved PSO algorithm to solve the problem.

Because of the global increase of climate change effects, floods are becoming more frequent and severer, especially in urban areas of coastal cities and islands where floodplains have turned into buildings because of rapid urbanisation, leading to a higher risk of damages. Urban heritage areas should be highly considered in the time of evacuation because of the vulnerability of streets and buildings and limitations on taking counteractions. Given these limitations, this study aims to propose a network of potential evacuation routes based on spatial configuration analysis of the heritage areas.

Penang Island's heritage site, namely, George Town, located on the northwest coast of Malaysia, is chosen as the case study. By using an approach of spatial configuration analysis using space syntax techniques in addition to considering the potential starting points for evacuation and flood risk map of the area, this study analysed the area's street network values for evacuation function during flood crisis time.

Potential evacuation routes were identified for flood disasters in the George Town heritage area. Furthermore, the proposed evacuation routes were evaluated in terms of time for evacuation by metric step-depth analysis of space syntax.

A few studies have focused on practical guidelines for evacuation routes based on spatial configuration analysis, an important yet neglected approach in this regard, especially concerning urban island areas. This study can contribute to providing strategies to reduce vulnerability and casualties in urban heritage areas.

Public open spaces (POS) in cities are often measured as a strength to enhance cities’ sustainability with a contribution to the three pillars: economic, social and environmental. Nevertheless, the importance of POS for disaster resilience is less recognised and remains under-rehearsed in the urban planning context. Within this context, this research paper aims to investigate the methods and approaches of using POS to enhance the coastal cities’ resilience to tsunamis through planning and designing interventions.

This study used the grounded theory as the research strategy. Accordingly, data collection involved 72 unstructured interviews covering a wide variety of participants related to the field of study including tsunami-affected communities, disaster resilience experts, urban planners, sociologists and coastal planners, in the context of Sri Lanka. The grounded theory coding procedure is used to analyse the data that includes transcripts, notes, maps and documents.

The analysis reveals that there is a significant potential to use POS to enhance the coastal cities’ resilience to tsunamis as an emergency evacuation directing point, as a primary place for emergency rescue, as an agent for temporary sheltering, as a facilitator for tsunami disaster mitigation and as a mediator to provide tsunami awareness. Finally, the findings propose five guiding factors for planning POS to enhance coastal cities’ disaster resilience to Tsunamis.

This paper introduces an innovative and unique approach for future urban planners and design professionals, to plan and design POS with a new direction towards disaster resilience while ensuring sustainability.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.