30 research outputs found
The Benefits of Information Sharing in Carrier-Client Collaboration
This dissertation includes three related papers to investigate different methods that can help transport providers improve their operational efficiency. The first paper models and measures the profit improvement trucking companies can achieve by collaborating with their clients to obtain advance load information (ALI). The core research method is to formulate a comprehensive and flexible mixed integer mathematical model and implement it in a dynamic rolling horizon context. The findings illustrate that access to the second day ALI can improve the profit by an average of 22%. We also found that the impact of ALI depends on radius of service and trip length but statistically independent of load density and fleet size.
The second paper investigates the following question of relevance to truckload dispatchers striving for profitable decisions in the context of dynamic pick-up and delivery problems: since not all future pick-up/delivery requests are known with certainty, how effective are alternative methods for guiding those decisions? We propose an intuitive policy and integrate it into a new two-index mixed integer programming formulation, which we implement using the rolling horizon approach. On average, in one of the practical transportation network settings, the proposed policy can, with just second-day ALI, yield an optimality ratio equal to almost 90% of profits in the static optimal solution. We enhance the proposed policy by adopting the idea of a multiple scenario approach. In comparison to other dispatching methods, our proposed policies were found to be very competitive in terms of solution quality and computational efficiency.
Finally, inspired by a real-life third party logistic provider, the third paper addresses a dynamic pickup and delivery problem with full truckload (DPDFL) for local operators. The main purpose of this work is to investigate the impact of potential factors on the carriersâ operational efficiency. These factors, which are usually under managerial influence, are vehicle diversion capability, the DPDFL decision interval, and how far in advance the carrier knows of clientsâ shipment requirements; i.e., ALI. Through comprehensive numerical experiments and statistical analysis, we found that the ALI and re-optimization interval significantly influence the total cost, but that diversion capability does not. A major contribution of this work is that we develop an efficient benchmark solution for the DPDFLâs static version by discretization of time windows. We observed that three-day ALI and an appropriate decision interval can reduce deviation from the benchmark solution to less than 8%
The Benefit of Information Sharing in a Logistics Outsourcing Context
The goal of this article is to examine the value of information sharing in outsourcing of logistics activities. Our examination is in the context of a fairly complex network in which location and capacity of carriers are considered. The current research also examines the moderating effect of network settings on the benefit of information sharing. A core component of our methodology is use of computational experiments to provide a variety of logistics network conditions under which we investigate information sharing value. The investigation involves comparing two strategies, namely full and no information sharing. Underlying the experiments are procedures to optimise the network under each strategy. The procedures are based on exact methods that combine integer linear programming with exhaustive enumeration. To gauge the robustness of the insights, we applied formal analysis of variance techniques to the data from the numerical experiments. The obtained insights are helpful to managers for selecting appropriate logistics service providers and level of information exchange
The Impact of Operating Systems and Environments on Build Results
LâintĂ©gration continue (IC) est une pratique dâingĂ©nierie logicielle permettant dâidentifier et de corriger les fautes logicielles le plus rapidement possible aprĂšs lâintĂ©gration dâun changement de code dans systĂšme de contrĂŽle de versions. Lâobjectif principal de lâIC est dâinformer
les dĂ©veloppeurs des consĂ©quences des changements effectuĂ©s dans le code. LâIC sâappuie sur diffĂ©rents systĂšmes dâexploitation et environnements dâexĂ©cution pour vĂ©rifier si un systĂšme fonctionne toujours aprĂšs lâintĂ©gration des changements. Ainsi, de nombreux "builds" sont crĂ©Ă©s, alors que seulement quelques-uns rĂ©vĂšlent de nouvelles fautes. En dâautres termes, un phĂ©nomĂšne dâinflation des builds se produit, oĂč le nombre croissant de builds a un rendement
dĂ©croissant. Cette inflation rend lâinterprĂ©tation des rĂ©sultats des builds difficile, car lâinflation augmente lâimportance de certaines fautes, alors quâelle cache lâimportance dâautres. Cette thĂšse fait progresser notre comprĂ©hension de lâimpact des systĂšmes dâexploitation et
des environnements dâexĂ©cution sur les fautes des builds et le biais potentiel encouru Ă cause de lâinflation des builds par une Ă©tude Ă grande Ă©chelle de 30 millions de builds de lâĂ©cosystĂšme CPAN. Nous choisissons CPAN parce que CPAN fournit un riche ensemble de donnĂ©es pour lâanalyse automatisĂ©e des builds sur des douzaines dâenvironnements (versions de Perl) et systĂšmes dâexploitation. Cette thĂšse rapporte une analyse quantitative et qualitative sur
les fautes dans les builds pour classer ces fautes et trouver la raison de leur apparition. Nous observons : (1) lâĂ©volution des fautes des builds au fil du temps et rapportons que plus de builds sont effectuĂ©s, plus le pourcentage de fautes de builds diminue, (2) diffĂ©rents environnements et systĂšmes dâexploitation mettent en avant diffĂ©rentes fautes, (3) les rĂ©sultats des builds doivent ĂȘtre filtrĂ©s pour identifier des fautes fiables, et (4) la plupart des fautes des builds sont dus Ă leur dĂ©pendance Ă lâAPI. Les chercheurs et les praticiens devraient tenir
compte de lâimpact de lâinflation des builds lorsquâils analysent ou exĂ©cutent des builds.----------ABSTRACT: Continuous Integration (CI) is a software engineering practice to identify and correct a defect as soon as possible after a code change has been integrated into the version control system. The main purpose of CI is to give developers a quick feedback of code changes. These changes
build on different OSes and runtime environments to check backward compatibility as well as to check if the product still works with the new changes. So, many builds are performed, while only a few of them can identify new failures. In other words, a phenomenon of build inflation can be observed, where the increasing number of builds has diminishing returns in terms of identified failures vs. costs of running the builds. This inflation makes interpreting build results challenging as it increases the importance of some failures, while it hides the importance of others. This thesis advances our understanding of the impact of OSes and runtime environments on build failures and build inflation through a large-scale study of 30
million builds of the CPAN ecosystem. We choose CPAN because CPAN provides a rich data set for the analysis of automated builds on dozens of environments (Perl versions) and
operating systems. This thesis performs quantitative and qualitative analysis on build failures to classify these
failures and find out the reason of their occurrence. We observe: (1) the evolution of build failures over time and report that while more builds are being performed, the percentage of them identifying a failure drops, (2) different OSes and environments are not equally reliable,
(3) the build results of CI must be filtered to identify reliable failing data, (4) and most build failures are due to API dependency. Researchers and practitioners should consider the impact of build inflation when they are analyzing and-or performing builds
Anticipatory freight selection in intermodal long-haul round-trips
We consider the planning problem faced by Logistic Service Providers (LSPs) transporting freights periodically, using long-haul round-trips. In each round-trip, freights are delivered and picked up at different locations within one region. Freights have time-windows and become known gradually over time. Using probabilistic knowledge about future freights, the LSPâs objective is to minimize costs over a multi-period horizon. We propose a look-ahead planning method using Approximate Dynamic Programming. Experiments show that our approach reduces costs up to 25.5% compared to a single-period optimization approach. We provide managerial insights for several intermodal long-haul round-trips settings and provide directions for further research
Cobalt supported on dendronized magnetic nanoparticles: A new highly efficient and recyclable catalyst for the MizorokiâHeck crossâcoupling reaction
The Benefit of Information Sharing in a Logistics Outsourcing Context
The goal of this article is to examine the value of information sharing in outsourcing of logistics activities. Our examination is in the context of a fairly complex network in which location and capacity of carriers are considered. The current research also examines the moderating effect of network settings on the benefit of information sharing. A core component of our methodology is use of computational experiments to provide a variety of logistics network conditions under which we investigate information sharing value. The investigation involves comparing two strategies, namely full and no information sharing. Underlying the experiments are procedures to optimise the network under each strategy. The procedures are based on exact methods that combine integer linear programming with exhaustive enumeration. To gauge the robustness of the insights, we applied formal analysis of variance techniques to the data from the numerical experiments. The obtained insights are helpful to managers for selecting appropriate logistics service providers and level of information exchange
A study of build inflation in 30 million CPAN builds on 13 Perl versions and 10 operating systems
Relationship Between Rate of Access to Resources and Guidelines of Health Information and Quality of Life in Women Referring to Hospitals in Qom in 2016
Background & Objectives:Â In Iran, few studies have been conducted on health information sources. The aim of this study was to determine the relationship between rate of access to resources and guidelines of health information and quality of life in women referring to hospitals in Qom city in 2016.
Materials & Methods:Â This cross-sectional descriptive-analytical study was performed on 254 women referring to hospitals in the city of Qom in 2016. The subjects were selected via multi-stage sampling method. Data were collected by a researcher-made questionnaire on sources and guidelines of health information and the valid Quality of Life Questionnaire. The collected data were entered into SPSS V.20 software and were analyzed using Chi-square, ANOVA, and Pearson correlation coefficient tests.
Results:Â There was a significant negative correlation between the quality of life score and the use of the resources and guidelines of health information (r=-0.14, p=0.02), as with increasing the use of the resources and guidelines of health information, the score of quality of life of the subjects reduced. In addition, there was a significant relationship between educational level and type of the resources and guidelines of health information (p<0.02) so that, the people with university education were more likely to use more self-resources and mass media to obtain health information.
Conclusion:Â Given the significant relationship between quality of life and the use of the resources and guidelines of health information, people should be properly informed about and familiarized with the reliable sources and guidelines of health information that are suitable for their conditions and levels of literacy