Managing Delivery of Safeguarding Substances as a Mitigation Against Outbreaks of Pandemics

The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics.A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specic time period.A nonlinear binary mathematical programming model for the problem is formulated.The decision variables are binary ones that represent whether to choose a specic consumer,and design constraints are formulated to keep track of the chosen route.To better illustrate the problem,objective,and problem constraints,a real application case study is presented.The case study involves the optimum delivery of safeguarding substances to several hospitals in the Al-Gharbia Governorate in Egypt.The hospitals are selected to represent the consumers of safeguarding substances,as they are the rst crucial frontline for mitigation against a pandemic outbreak.A distribution truck is used to distribute the substances from the main store to the hospitals in specied required quantities during a given working shift.The objective function is formulated in order to maximize the total amount of delivered quantities during the specied time period.The case study is solved using a novel Discrete Binary Gaining Sharing Knowledge-based Optimization algorithm(DBGSK),which involves two main stages:discrete binary junior and senior gaining and sharing stages.DBGSK has the ability of nding the solutions of the introduced problem,and the obtained results demonstrate robustness and convergence toward the optimal solutions.

Overlapping Shadow Rendering for Outdoor Augmented Reality

Realism rendering methods of outdoor augmented reality(AR)is an interesting topic.Realism items in outdoor AR need advanced impacts like shadows,sunshine,and relations between unreal items.A few realistic rendering approaches were built to overcome this issue.Several of these approaches are not dealt with real-time rendering.However,the issue remains an active research topic,especially in outdoor rendering.This paper introduces a new approach to accomplish reality real-time outdoor rendering by considering the relation between items in AR regarding shadows in any place during daylight.The proposed method includes three principal stages that cover various outdoor AR rendering challenges.First,real shadow recognition was generated considering the sun’s location and the intensity of the shadow.The second step involves real shadow protection.Finally,we introduced a shadow production algorithm technique and shades through its impacts on unreal items in the AR.The selected approach’s target is providing a fast shadow recognition technique without affecting the system’s accuracy.It achieved an average accuracy of 95.1%and an area under the curve(AUC)of 92.5%.The outputs demonstrated that the proposed approach had enhanced the reality of outside AR rendering.The results of the proposed method outperformed other state-of-the-art rendering shadow techniques’outcomes.