An evaluation of three DoE-guided meta-heuristic-based solution methods for a three-echelon sustainable distribution network

This article evaluates the efficiency of three meta-heuristic optimiser (viz. MOGA-II, MOPSO and NSGA-II)-based solution methods for designing a sustainable three-echelon distribution network. The distribution network employs a bi-objective location-routing model. Due to the mathematically NP-hard nature of the model a multi-disciplinary optimisation commercial platform, modeFRONTIER®, is adopted to utilise the solution methods. The proposed Design of Experiment (DoE)-guided solution methods are of two phased that solve the NP-hard model to attain minimal total costs and total CO2 emission from transportation. Convergence of the optimisers are tested and compared. Ranking of the realistic results are examined using Pareto frontiers and the Technique for Order Preference by Similarity to Ideal Solution approach, followed by determination of the optimal transportation routes. A case of an Irish dairy processing industry’s three-echelon logistics network is considered to validate the solution methods. The results obtained through the proposed methods provide information on open/closed distribution centres (DCs), vehicle routing patterns connecting plants to DCs, open DCs to retailers and retailers to retailers, and number of trucks required in each route to transport the products. It is found that the DoE-guided NSGA-II optimiser based solution is more efficient when compared with the DoE-guided MOGA-II and MOPSO optimiser based solution methods in solving the bi-objective NP-hard three-echelon sustainable model. This efficient solution method enable managers to structure the physical distribution network on the demand side of a logistics network, minimising total cost and total CO2 emission from transportation while satisfying all operational constraints

Enterocolitis necrotizante en recién nacidos ingresados en el Servicio de Neonatología del Hospital Escuela "Carlos Roberto Huembes" en el período comprendido de Enero 2011 a Diciembre 2013

La enterocolitis necrotizante en el recién nacido presenta un amplio espectro de manifestaciones clínicas, caracterizándose principalmente por la tríada de distensión abdominal, sangramiento gastrointestinal y neumatosis intestinal. A pesar del avance en el cuidado intensivo neonatal, persiste como una enfermedad grave, que afecta habitualmente al recién nacido pretérmino, especialmente de muy bajo peso

A MULTI-OBJECTIVE TRAIN SCHEDULING MODEL AND SOLUTION

Train scheduling is a highly complex task, since the physical railroad network is shared by a large number of both freight and passenger trains. This study develops a multi-objective optimization model for the passenger train-scheduling problem on a railroad network that includes single and multiple-tracks, as well as multiple platforms with different train capacities. In this study, lowering the fuel consumption cost is used as the measure of satisfaction of the railroad company and shortening the total passenger-time is being regarded as the passenger satisfaction criterion. The solution of the problem consists of two steps. To solve the problem, the Pareto frontier first is determined. Based on the obtained Pareto frontier, detailed multi-objective optimization then is performed using the distance-based method with three types of distances. A simple numerical example is given to illustrate the model, solution method and results. The sensitivity of the solutions was also examined. To demonstrate the applicability of the model and solution procedure, the results from 21 worked numerical examples are given

Building website certificate mental models

Expert security users make safer online decisions. However, average users do not have mental models for browser security and web certificates. Thus, they may make unsafe decisions online, putting their sensitive information at risk. Users can learn about browser security and their mental models can be developed using information visualization. We introduce an interactive interface designed for building mental models of web certificates for the average user, through visualization and interaction. This model was implemented to facilitate learning with a Mental Model Builder (MMB). The interface underwent a cognitive walkthrough usability inspection to evaluate the learnability and efficacy of the program. We found that there were unique and useful elements to our visualization of browser certificates. Thus, a 2nd generation interface was created and user-tested. Results show that it was successful in building mental models, and users made safer decisions about trusting websites

Mitigating Inadvertent Insider Threats with Incentives

Abstract. Inadvertent insiders are trusted insiders who do not have malicious intent (as with malicious insiders) but do not responsibly managing security. The result is often enabling a malicious outsider to use the privileges of the inattentive insider to implement an insider attack. This risk is as old as conversion of a weak user password into root access, but the term inadvertent insider is recently coined to identify the link between the behavior and the vulnerability. In this paper, we propose to mitigate this threat using a novel risk budget mechanism that offers incentives to an insider to behave according to the risk posture set by the organization. We propose assigning an insider a risk budget, which is a specific allocation of risk points, allowing employees to take a finite number of risk-seeking choice. In this way, the employee can complete her tasks without subverting the security system, as with absolute prohibitions. In the end, the organization penalizes the insider if she fails to accomplish her task within the budget while rewards her in the presence of a surplus. Most importantly. the risk budget requires that the user make conscious visible choices to take electronic risks. We describe the theory behind the system, including specific work on the insider threats. We evaluated this approach using human-subject experiments, which demonstrate the effectiveness of our risk budget mechanism. We also present a game theoretic analysis of the mechanism