Managing Materiel Distribution in an Uncertain Environment

NPS NRP Executive SummaryManaging Materiel Distribution in an Uncertain EnvironmentN4 - Fleet Readiness & LogisticsThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Tekoälyn hyödyntäminen toimitusketjun riskienhallinnassa

Tämä kandidaatintutkielma käsittelee tekoälyn hyödyntämistä toimitusketjun riskienhallinnassa. Tutkimuksen tavoitteena on selvittää, miten tekoäly voi auttaa tunnistamaan, arvioimaan ja hallitsemaan toimitusketjun riskejä, parantaa ennustettavuutta ja tehostaa reagointikykyä mahdollisissa häiriötilanteissa. Työssä tarkastellaan erilaisia tekoälyn sovelluksia, kuten koneoppimista ja syväoppimista, ja niiden soveltuvuutta eri osa-alueille toimitusketjun riskienhallinnassa. Tutkielman tavoitteena on pohtia kirjallisuuskatsauksen avulla, miten tekoälyä hyödynnetään toimitusketjujen riskienhallinnassa. Yhdistän tekstissä toimitusketjujen riskienhallinnan, tekoälyn ja toimitusketjujen kirjallisuuden. Tutkielma keskittyy tekoälysovelluksien hyödyntämiseen ja mahdollisiin haasteisiin toimitusketjun riskienhallinnassa. Tutkimuskysymys on: Miten tekoälyä voidaan hyödyntää toimitusketjun riskienhallinnassa? Tutkimuskysymyksen avulla pyrin hahmottamaan tekoälyn tarvetta ja mahdollisia haasteita. Tutkimukset osoittavat, että tekoäly voi parantaa riskien tunnistamista ja hallintaa toimitusketjussa. Tekoäly mahdollistaa myös jatkuvan oppimisen ja adaptiivisen päätöksenteon, mikä on tärkeää toimitusketjun dynaamisessa ja monimutkaisessa ympäristössä

A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. This paper aims to develop a recovery planning approach in a three-tier manufacturing supply chain, which has a single supplier, manufacturer, and retailer under an imperfect production environment, in which we consider three types of sudden disturbances: demand fluctuation, and disruptions to production and raw material supply, which are not known in advance. Firstly, a mathematical model is developed for generating an ideal plan under imperfect production for a finite planning horizon while maximizing total profit, and then we re-formulate the model to generate the recovery plan after happening of each sudden disturbance. Considering the high commercial cost and computational intensity and complexity of this problem, we propose an efficient heuristic, to obtain a recovery plan, for each disturbance type, for a finite future period, after the occurrence of a disturbance. The heuristic solutions are compared with a standard solution technique for a considerable number of random test instances, which demonstrates the trustworthy performance of the developed heuristics. We also develop another heuristic for managing the combined effects of multiple sudden disturbances in a period. Finally, a simulation approach is proposed to investigate the effects of different types of disturbance events generated randomly. We present several numerical examples and random experiments to explicate the benefits of our developed approaches. Results reveal that in the event of sudden disturbances, the proposed mathematical and heuristic approaches are capable of generating recovery plans accurately and consistently

Towards pre-emptive resilience in military supply chains: a compromise decision support model-based approach

The complex and dynamic nature of military supply chains (MSC) requires constant vigilance to sense potential vulnerabilities. Several studies have employed decision support models for the optimization of their operations. These models are often limited to a best single-point solution unsuitable for complex MSC constellations. In this article, the authors present a novel approach based on decision support models to explore a range of satisficing solutions against disruptions in MSCs using a compromise Decision Support Problem (cDSP) construct and Decision Support in the Design of Engineered Systems (DSIDES). Two cases were evaluated: (1) a baseline scenario with no disruption and (2) with disruption to achieve target values of three goals: (1) minimizing lead time, (2) maximizing demand fulfilment and (3) maximizing vehicle utilization. The results obtained in Case 1 identified a more stable solution space with minimal deviations from the target value, while in Case 2 the solution space was unstable with deviations from the target values

Two-stage security screening strategies in the face of strategic applicants, congestions and screening errors

Abstract In a security screening system, a tighter screening policy not only increases the security level, but also causes congestion for normal people, which may deter their use and decrease the approver's payoff. Adapting to the screening policies, adversary and normal applicants choose whether to enter the screening system. Security managers could use screening policies to deter adversary applicants, but could also lose the benefits of admitting normal applicants when they are deterred, which generates a tradeoff. This paper analyzes the optimal screening policies in an imperfect two-stage screening system with potential screening errors at each stage, balancing security and congestion in the face of strategic normal and adversary applicants. We provide the optimal levels of screening strategies for the approver and the best-response application strategies for each type of applicant. This paper integrates game theory and queueing theory to study the optimal two-stage policies under discriminatory and non-discriminatory screening policies. We extend the basic model to the optimal allocation of total service rate to the assumed two types of applicants at the second stage and find that most of the total service rate are assigned to the service rate for the assumed "Bad" applicants. This paper provides some novel policy insights which may be useful for security screening practices

Strategies to Minimize the Bullwhip Effect in the Electronic Component Supply Chain

Supply chain leaders in the information technology industry face challenges regarding their ability to mitigate amplified demand and supply variability in a supply chain network--the bullwhip effect--and reduce adverse implications on their component supply chain networks. The purpose of this multiple case study was to explore the strategies supply chain leaders in the United States used to reduce the bullwhip effect. Bullwhip effect theory served as the conceptual framework. Participants in the study were 5 purposefully selected supply chain leaders in the state of Texas who successfully implemented strategies to reduce the bullwhip effect on their networks. Data were collected from semistructured interviews and analysis of documents from the participants\u27 websites. The data were analyzed using the 5 data analysis steps consistent with Yin\u27s approach: collection, stratification, reassembly, interpretation, and conclusion. Four themes emerged from data analysis: (a) collaboration strategy, (b) communication strategy, (c) component shortage reduction strategy, and (d) resource management strategy. Supply chain leaders might use the findings of this study to reduce the bullwhip effect within their networks and improve their profitability. The implications for positive social change include the potential for leaders to improve environmental sustainability by using effective supply chain strategies to reduce the accumulation of excess inventories, reduce transportation fuel usage, and lessen the consumption of natural resources

Naval Research Program 2019 Annual Report

NPS NRP Annual ReportThe Naval Postgraduate School (NPS) Naval Research Program (NRP) is funded by the Chief of Naval Operations and supports research projects for the Navy and Marine Corps. The NPS NRP serves as a launch-point for new initiatives which posture naval forces to meet current and future operational warfighter challenges. NRP research projects are led by individual research teams that conduct research and through which NPS expertise is developed and maintained. The primary mechanism for obtaining NPS NRP support is through participation at NPS Naval Research Working Group (NRWG) meetings that bring together fleet topic sponsors, NPS faculty members, and students to discuss potential research topics and initiatives.Chief of Naval Operations (CNO)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.