Scenario based logistic capacity assessment for disaster preparedness

Two-echelon logistics distribution region partitioning problem based on a hybrid particle swarm optimization–genetic algorithm

This paper presents a methodological approach to solving the fuzzy capacitated logistic distribution center problem, with a focus on the optimal selection of distribution centers to meet the demands of multiple plants. The distribution centers are characterized by fixed costs and capacities, while plant demands are modeled using fuzzy triangular membership functions. The problem is mathematically formulated by converting fuzzy demands into crisp values, providing a structured framework for addressing uncertainty in logistic planning. To support future research and facilitate comparative analysis, 20 benchmark problems were generated, filling a gap in the existing literature. Three distinct artificial bee colony algorithm variants were hybridized with a heuristic: one using the best solution per iteration, another incorporating chaotic mapping and adaptive procedures, and the third employing convergence and diversity archives. An experimental design based on Taguchi's orthogonal arrays was employed for optimizing the algorithm parameters, ensuring systematic exploration of the solution space. The developed methods offer a comprehensive toolkit for addressing complex, uncertain demands in logistic distribution, with code provided for reproducibility.Key contributions include:•Development of a fuzzy model for the selection of distribution centers with fixed costs and capacities under uncertain plant demands.•Generation of 20 benchmark problems to advance research in the fuzzy capacitated logistic distribution center problem domain.•Integration of a heuristic approach with three distinct ABC algorithm variants, each contributing unique methodological insights.

Preference-based regret three-way decision method on multiple decision information systems with linguistic Z-numbers

Most current information fusion techniques focus on adding as many different information sources as possible, and then observe the performance of the final fused result. They generally do not concern whether a new information source is useful or not until it is added into the fusion system. The statistical meta-analysis offers a set of quantitative techniques that permit synthesizing a variety of independent information sources. Using the statistical meta-analysis, this paper presents a method that can provide fusion criteria to foretell the effect of adding a new information source in terms of statistical type Ⅰ,type Ⅱerrors and an expected error cost before the source is actually combined. Implementation results confirm the highly accurate prediction power of the proposed models.

As an organization grows through mergers and acquisitions and through the integration of independently designed information sub-systems, it could find itself faced with a collection of databases implemented on heterogeneous database management systems. This paper presents a system to provide integrated access to multiple, independently designed databases through a portable natural language front-end and a multiple database access system back-end.The overall system is divided into a natural language interface (NLI) front-end and a multiple database access system (MDAS) back-end. The MDAS integrates the various conceptual views into a single global external schema. In a prototype of the overall system, the NLI will accept a natural language query and produce a relational calculus query expression over a global external schema. The MDAS will construct the response to the query by accessing the separate constituent databases through the local database management systems (DBMS's).

Blood transfusion is a common medical intervention. For patients with acute critical bleeding, large volume "massive" transfusion (MT) is required, and is potentially life-saving. However, the evidence-base for transfusion practice, particularly for critical bleeding/MT management, is relatively weak, and has confounded the development of clinical best practice recommendations. The aim was to address this evidence gap by building the Australian and New Zealand Massive Transfusion Registry (ANZ-MTR). We describe how data collection, standardisation and interoperability of data sourced from multiple electronic information systems are managed, and share the lessons learned. The ANZ-MTR is a database of routine electronic hospital admission information, laboratory test results, transfusion records and outcomes of adults (18 years and older) who have received a MT for any cause of acute critical bleeding, including trauma, major surgery, obstetric or gastrointestinal haemorrhage. Source data are provided by participating hospitals and are harmonised by the registry. Since its launch in 2011, the ANZ-MTR has captured over 9200 MT episodes from 29 hospitals.What can be learned from this case:Effective communication with all custodians of the source data has been fundamental to the success of the registry. A preeminent outcome of this success is the current expansion of the registry to become the National Transfusion Dataset, which will capture comprehensive data for all transfusions.Implications for health information management practice:The ANZ-MTR illustrates that complex and varied arrays of routinely collected clinical and hospital administrative data from multiple electronic information systems can be consolidated into a resource-rich clinical database.

Bangkalan Regency faces serious challenges due to flood disasters that periodically threaten the safety and welfare of the community. The flood phenomenon in this area is caused by a complex combination of geographic and climate factors, including increased extreme rainfall and the dynamics of sea level rise. Annual floods not only cause infrastructure damage but also threaten the livelihoods and lives of residents living around the river flow. This study aims to develop an innovative flood early warning system using the K-Nearest Neighbors (KNN) method to predict potential disasters before floods occur. By using water flow data analysis and machine learning algorithms, this system is designed to provide accurate and timely early estimates. The main advantage of this study is its ability to proactively mitigate disaster risks using modern computer technology. The study produced a prototype of a flood detection and simulation system that can help local governments, related agencies, and the Bangkalan community in taking preventive and mitigation actions at an earlier stage. Therefore, this system is expected to make a significant contribution to reducing the impact of disasters and protecting the lives of Bangkalan Regency residents.

This paper describes an improved genetic algorithm for solving location problem of logistic distribution center for perishable products when restrictive area exists. The model considers the impact of the perishability as part of the overall distribution cost, and a heuristic approach on sub distribution areas and feasible routes is combined with genetic algorithm to solve the problem. Computational results are reported on location problem of logistic distribution center derived from benchmark instances with restrictive area.

The growth in population and private vehicles in Surabaya has caused a significant increase in traffic congestion. To overcome this problem, the Surabaya City government implemented the Suroboyo Bus public transportation policy as an alternative solution. This research aims to evaluate the impact of this policy in reducing traffic jams in the city of Surabaya. The research methods used include secondary data analysis from related agencies, Suroboyo Bus user satisfaction surveys, as well as field observations at several main congestion points. The research results show that the implementation of Suroboyo Bus contributed to reducing the volume of private vehicles by 12% on main routes and increasing public interest in public transportation. However, the effectiveness of this policy still faces challenges, especially in terms of integration of transportation modes and service area coverage. In conclusion, the Suroboyo Bus policy has great potential to reduce congestion if supported by infrastructure development and increasing public awareness of the use of public transportation.

The selection of a central warehouse location is a critical decision in logistics systems, as it is influenced by business process uncertainty, cost optimization, and environmental considerations such as CO? emissions. In the context of Bali Province, logistics activities involving the transportation of goods from Java are closely associated with these challenges. Addressing environmental concerns through sustainable logistics principles requires an analytical approach that accounts for uncertainty in logistics operations. This study applies simulation-based stochastic modeling using AnyLogic software integrated with Geographic Information System (GIS) features to evaluate alternative central warehouse locations based on CO? emission calculations. The logistics distribution model incorporates both land and sea transportation modes, reflecting the real distribution conditions between Java and Bali. The simulation results indicate that Mangupura is the preferred location for the central warehouse, despite Negara having a shorter average transportation distance.

Multimedia in the radiology environment: Current concept

The National Weather Service (NWS) maintains the National Operational Hydrologic Remote Sensing Center, based in Minneapolis, to generate operational hydrologic products from in situ and remotely sensed snow cover data sets. The Center maintains an Airborne Snow Survey Program, a Satellite Hydrology Program, and a Snow Estimation and Updating Program. In all three programs, the Center relies heavily on the use of multiple Geographic Information Systems (GIS) to process, analyze, and distribute spatial snow cover data sets. Real-time, airborne snow water equivalent data and satellite areal extent of snow cover data are used operationally by the National Weather Service, the U.S. Army Corps of Engineers and other Federal, state, and private agencies when issuing spring flood outlooks, water supply outlooks, river and flood forecasts, and reservoir inflow forecasts. The remotely sensed and interpolated, gridded, snow water equivalent data products are generated by hydrologists in the Minneapolis office and distributed electronically, in near real-time, to NWS and non-NWS end-users in both alphanumeric and graphic format. The reliable, real-time, snow water equivalent information is critical to water managers and disaster emergency services officials who are required to make decisions with regard to snow melt flooding, reservoir regulation, and water supply allocation.KeywordsSnow CoverGeographic Information SystemSnow Water EquivalentNational Weather ServiceGeographic Resource Analysis Support SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

ABSTRACTThe Indian Ocean region, in recent years, has witnessed a proliferation of information centers which have emerged in response to various sub-regional requirements and sometimes representing diverse interest groups. This paper highlights the gaps in regional maritime domain awareness (MDA) and argues that the multiple disparate information systems have not contributed to improving overall maritime safety and security in the Indian Ocean region. It puts forward a case for a pan-Indian Ocean information grid that could integrate the various information sources to provide comprehensive MDA for the region.

According to the requirements of the multiple municipal management information system integration, the principle and method for realizing cross-domain single sign-on in the municipal portal system is proposed. Based on analysis of the common single sign-on technology, this paper discusses designs of a CAS-based municipal portal single sign-on system. By storing user's authentication information on CAS server, this method solves the problems in cross-domain authentication and realizes the cross-domain single sign-on. Practical application shows that through the improvement of common CAS, the authentication and authorization can be separated, and municipal information system integration and sharing can be realized through established single sign-on municipal portal, thus providing convenience for the users to quickly access to the resources.

It is our greatest honor to edit this special section entitled “Selected Papers of ICEBE 2007”, for the Journal of Service Oriented Computing and Applications. Our main objective is to disseminate inspiring work that addresses the problem of engineering e-Business systems. E-Business has emerged as an important computing paradigm in digital societies. The paradigm imposes many interesting challenges to both the research community and the industry. These challenges range from the reliable integration of e-services to trustworthy transactions of e-retailing. Addressing these challenges requires the cross fertilization of multiple disciplines, including databases, software engineering, networking, grid computing, security, machine intelligence and information systems. This special section publishes two selected best papers presented in the IEEE International Conference on e-Business Engineering in 2007. The first paper presents an inspiring management framework to evaluate the trust and reputation of complex service-oriented applications. The second paper presents a novel entropy-based algorithm to provide reliable recommendation on B2B e-commerce services. We would like to thank all the referees who have worked hard to review each paper in a timely fashion, and provided authors with constructive comments on how to improve the work to its highest quality. We trust that you will find the articles of this special section interesting and informative.