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The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.

The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.

It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.

This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.

The rapid development of smart cities and green logistics has stimulated a lot of research on reverse logistics, and the diversified data also provide the possibility of innovative research on location-routing problem (LRP) under reverse logistics. The purpose of this paper is to use panel data to assist in the study of multi-cycle and multi-echelon LRP in reverse logistics network (MCME-LRP-RLN), and thus reduce the cost of enterprise facility location.

First, a negative utility objective function is generated based on panel data and incorporated into a multi-cycle and multi-echelon location-routing model integrating reverse logistics. After that, an improved algorithm named particle swarm optimization-multi-objective immune genetic algorithm (PSO-MOIGA) is proposed to solve the model.

There is a paradox between the total cost of the enterprise and the negative social utility, which means that it costs a certain amount of money to reduce the negative social utility. Firms can first design an open-loop logistics system to reduce cost, and at the same time, reduce negative social utility by leasing facilities.

This study provides firms with more flexible location-routing options by dividing them into multiple cycles, so they can choose the right option according to their development goals.

This research is a pioneering study of MCME-LRP-RLN problem and incorporates data analysis techniques into operations research modeling. Later, the PSO algorithm was incorporated into the crossover of MOIGA in order to solve the multi-objective large-scale problems, which improved the convergence speed and performance of the algorithm. Finally, the results of the study provide some valuable management recommendations for logistics planning.

The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making.

It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake.

The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering.

The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs.

This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response.

This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

An increasing trend in residential property markets is the concept of planned residential community developments, offering a range of services not available to the existing residential property markets in that given location. The purpose of this paper is to analyse a number of planned residential community developments in a major city to determine the demand for these developments and the impact they have in relation to price premiums and the overall residential property market.

This study has identified four planned residential developments in the Sydney property market and all sale transactions in these developed estates or unit complexes have been analysed and compared to the sales transactions in the residential areas immediately adjoining the planned residential developments. These sales represent all sales transactions in the study areas and this database has enabled a comparison based on price trends, average annual capital return and price volatility.

Results from this study have shown that residential property buyers are prepared to pay a premium for property in a planned residential community, despite the availability of cheaper housing within immediately adjoining locations, with this premium being maintained over time. The study also shows that buyers are prepared to purchase a property in a planned residential estate even though the adjoining areas are not considered to be as desirable, and in time the planned residential estate can increase the price of residential property in the adjoining areas.

Although the sales data for two of the planned residential developments only covers the period 1999‐2004, this limitation is offset by the greater time period of sales transactions for the other two planned residential estates in the study. The limited sale period is due to the relatively new nature of these developments in Sydney, Australia.

The research has indicated that, in developed residential property markets, consumers will pay a premium for property that meets their lifestyle or security requirements, irrespective of the actual location of the development.

The research in competitive facility location (CFL) is quite dynamic, both from a problem formulation and an algorithmic point of view. Research direction has changed immensely over the years to address various competitive challenges. This study aims to explore CFL literature to highlight these research trends, important issues and future research opportunities.

This study utilises the Scopus database to search for related CFL models and adopts a five-step systematic approach for the review process. The five steps involve (1) Article Identification and keyword selection, (2) Selection criteria, (3) Literature review, (4) Literature analysis and (5) Research studies.

The paper presents a comprehensive review of CFL modelling efforts from 1981 to 2021 to provide a depth study of the research evolution in this area. The published articles are classified based on multiple characteristics, including the type of problem, type of competition, game-theoretical approaches, customer behaviour, decision space, type of demand, number of facilities, capacity and budget limitations. The review also highlights the popular problem areas and dedicated research in the respective domain. In addition, a second classification is also provided based on solution methods adopted to solve various CFL models and real-world case studies.

The paper covers 40 years of CFL literature from the perspective of the problem area, CFL characteristics and the solution approach. Additionally, it introduces characteristics such as capacity limit and budget constraint for the first time for classification purposes.

Materials supply is one of the important elements in construction operation and a major factor affecting the quality of construction projects. Many industries look to manage materials effectively by attempting to integrate logistics processes into logistics chains of suppliers and customers. Logistics processes, being crucial for successful completion of construction projects, but in fact, auxiliary, are often entrusted to external professionals specialised in logistic services, such as logistics centres. However, this tendency is yet to be developed in construction. The purpose of this paper is to develop a simulation framework for the examination of potential improvements of logistics performance using logistics centres.

A case study approach was adopted with computer simulation using Flexsim. Data of vehicle movements were collected during construction on-site from the start of construction to “hand-over” to the building owner.

The ideal location of a logistics centre is identified using vehicle movements data collected on the site. The potential improvements of the planned centre are then evaluated by simulating various scenarios of vehicle movements. The enclosed results from the simulations indicate that using a logistics centre will reduce waste for the construction project considered.

The paper emphasises that creating a logistics centre for a project can improve construction logistics performance, by consolidating and optimizing both off-site and on-site logistics, especially when the site condition is prohibitive (small footprint with limited loading bay area). Establishing logistics centres may help find ways of making the overall construction project more effective by improving the management of materials.

With the introduction in 1988 of a system of site‐based management in England and Wales, schools are now operating in a radically altered planning context in which responsibility for strategic planning has been delegated from local education authorities (LEAs) to individual schools. Although school development planning has been widely adopted by LEAs in the UK as a rational approach to site‐based planning, indicative research suggests that strategic planning in a sample of schools operating in the newly decentralized environment has been slower to develop in practice than originally anticipated. Evidence of a lack of a coherent planning process in schools casts doubt on their ability to operate successfully in the strategic vacuum likely to be created if the gradual demise of LEAs continues. Suggests that if schools are to take full advantage of the opportunities offered by site‐based management to plan and sustain their own long‐term improvement and development, a thorough review may be needed by central government of their existing laissez faireattitudes towards site‐based planning, if there is not to be considerable long‐term damage to the national education service as a whole.

The purpose of this paper is to present a spatial decision support system (SDSS) to be used by the local authorities of a city in the planning and response phase of a disaster. The SDSS focuses on the management of public spaces as a resource to increase a vulnerable population’s accessibility to essential goods and services. Using a web-based platform, the SDSS would support data-driven decisions, especially for cases such as the COVID-19 pandemic which requires special care in quarantine situations (which imply walking access instead of by other means of transport).

This paper proposes a methodology to create a web-SDSS to manage public spaces in the planning and response phase of a disaster to increase the access to essential goods and services. Using a regular polygon grid, a city is partitioned into spatial units that aggregate spatial data from open and proprietary sources. The polygon grid is then used to compute accessibility, vulnerability and population density indicators using spatial analysis. Finally, a facility location problem is formulated and solved to provide decision-makers with an adaptive selection of public spaces given their indicators of choice.

The design and implementation of the methodology resulted in a granular representation of the city of Lima, Peru, in terms of population density, accessibility and vulnerability. Using these indicators, the SDSS was deployed as a web application that allowed decision-makers to explore different solutions to a facility location model within their districts, as well as visualizing the indicators computed for the hexagons that covered the district’s area. By performing tests with different local authorities, improvements were suggested to support a more general set of decisions and the key indicators to use in the SDSS were determined.

This paper, following the literature gap, is the first of its kind that presents an SDSS focused on increasing access to essential goods and services using public spaces and has had a successful response from local authorities with different backgrounds regarding the integration into their decision-making process.

Factory outlet shopping centres are one of a number of new “out‐of‐town centre” retail formats within the UK. Outlines their major characteristics and origins within the USA, describes current developments within the UK and focuses on the planning issues raised by these developments.