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Blood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.

This study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.

The results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.

This study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.

This study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

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 purpose of this paper is to study the following two issues regarding blockchain crowdsourcing. First, to design smart contracts with lower consumption to meet the needs of blockchain crowdsourcing services and also need to design better interaction modes to further reduce the cost of blockchain crowdsourcing services. Second, to design an effective privacy protection mechanism to protect user privacy while still providing high-quality crowdsourcing services for location-sensitive multiskilled mobile space crowdsourcing scenarios and blockchain exposure issues.

This paper proposes a blockchain-based privacy-preserving crowdsourcing model for multiskill mobile spaces. The model in this paper uses the zero-knowledge proof method to make the requester believe that the user is within a certain location without the user providing specific location information, thereby protecting the user’s location information and other privacy. In addition, through off-chain calculation and on-chain verification methods, gas consumption is also optimized.

This study deployed the model on Ethereum for testing. This study found that the privacy protection is feasible and the gas optimization is obvious.

This study designed a mobile space crowdsourcing based on a zero-knowledge proof privacy protection mechanism and optimized gas consumption.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

Increasing competition in the market causes continued pressures for many companies to control or reduce costs. This has led to various responses by companies to seek more efficient operating models, in which the location where activities are performed has become a key determinant. The fast pace at which many low‐cost regions are developing into acceptable business environments has offered enormous opportunities for companies to change their geographic network of operations. The result is an ongoing shift of activities from welldeveloped, but high‐cost areas to low‐cost locations elsewhere in the world. This paper describes the relocation trends in the last decade, the drivers for cost reduction and the responses of companies. A location evaluation approach is described which helps to understand the cost and quality of doing business in various locations. Typically, there is a trade‐off between those two dimensions: low‐cost locations offer lower quality, whereas higher‐quality locations are more expensive. The challenge for companies aiming at cost reduction is to identify those locations where costs are low and quality is at an acceptable level.

This survey is similar to, though broader in scope than, a survey on monograph locations held in 1974. For this survey the broadest possible definition of ‘location’ was used including positive locations from our own and published union lists and speculative locations (including cases where, for example, it is suggested that the borrower apply to the originating body for such items as reports or theses). All categories of material have been covered in this study: monographs, serials and the various smaller categories that mostly come under the heading of ‘Miscellaneous Records’ at the Lending Division.

This article presents an integrated methodology for the inclusion of a facility′s interactions with the outside environment, and the impact of those interactions on the location of entrances and exits within the facility. For example, the outside interactions generated by shipping and receiving activities will significantly influence the location of facility ingress/egress points. The “practical layout planning” (PLP) methodology integrates both layout construction and improvement techniques. The principal idea in this methodology is that departments within a facility be “condensed” into a number of “points”. In the layout construction phase, the relative location of these points is determined using multifacility location theory, where the facility′s interactions with the outside environment are represented by “contact points” and the departments in the layout are analogous to the new facilities to be located. Once these relative departmental positions are obtained, the “points” are then adjusted for areas to obtain a constructed layout. In the improvement technique, intra‐departmental flows are optimised by the optimal location of ingress/egress points which are determined by again using multifacility location theory. Interdepartmental flow is optimised by minimising the distance between departments as indicated by their closest ingress/egress points. The objective is to obtain a minimum total flow‐cost by interchanging departmental locations without violating physical constraints. The PLP methodology is demonstrated with a modest example.

This article constructs a distribution’s location model, from the perspective of a firm’s customers, suppliers, and employees, by applying a systematic quality function deployment (QFD) approach. The proposed approach aims to assist a distribution company’s location decision in selecting an optimal location that satisfies the overall location requirements. The QFD procedure began by collecting possible candidate location requirements, followed by conducting the first stage of a sampling survey to identify the secondary location requirements. These were then sorted into major categories of location requirements. Then, the location evaluating criteria were derived from the location requirements and a central relationship matrix was established to display the degree of relationship between each pair of location requirement and location evaluating criterion. Furthermore, the second stage of a sampling survey was conducted to collect data for computing the importance weighting for each category of location requirement. During transformation of the QFD, the importance degree and the normalized importance degree of each location criterion were computed, respectively. The normalized importance degree was, finally, used as the evaluating weight in a distribution company’s location model for the analysis of location evaluation. An empirical study regarding the location decision for a distribution center in Taiwan was provided to demonstrate the proposed approach.

The increasing number of context aware services, which depend on various multimodal sensing, processing and actuating techniques, technologies and formats ask for a physical framework that is able to handle their heterogeneity. Thereto, we propose a context model bridging the semantic gaps between context aware services. In addition we propose a simple system architecture of Distribution Servers and Transformation Servers that bridge semantic gaps among context aware services. Applying our framework we solve the heterogeneity problem existing for location services. Location is typically a form of context where heterogeneity is a problem.

The location‐allocation problem involves multiple shipping destinations, with known demands for a given product and known transportation costs from sources to destinations. The problem is to determine the number of facilities and their locations in order to best service the shipping destinations. This paper presents an approach to facility location which allows the analysis of multiple conflicting goals as an extension of previous solution approaches. Specifically, the paper applies the branch and bound integer goal programming approach to the location‐allocation problem.