Improved artificial bee colony algorithm based on escaped foraging strategy

This paper presents an improved artificial bee colony algorithm. Under the framework of the basic artificial bee colony algorithm, this paper redefines the artificial bee colony and introduces search strategies for group escape and foraging based on Levy flight. The proposed algorithm is named artificial bee colony algorithm based on escaped foraging strategy (EFSABC).There are different strategies for scout bees, onlookers, and free bees searching for honey sources in the EFSABC: all working bees relinquish old honey sources due to disturbance, and select different routines to seek new honey sources. Sixteen typical high-dimensional standard functions are used to verify the effectiveness of the proposed algorithm. The EFSABC algorithm outperforms the traditional artificial bee colony algorithm in all aspects.     

Robustness of asymptotic accelerated life test plans to small‐sample settings

Much of the statistical literature on optimal test planning for accelerated life testing utilize asymptotic methods to derive optimal test plans. While sufficient effort is made to assess the robustness of these test plans to the choice of design parameters and distribution assumptions, there is very little literature on the performance of asymptotic test plans relative to small samples (on the order of 10‐15 samples). An alternative concern is that the asymptotic test plans may not necessarily be the true “optimal” test plan for a given sample size. The purpose of this research is to present exact or “near‐exact” methods for developing test plans and compare the performance of these test plans with corresponding asymptotic test plans in small‐sample settings. The optimal location of design points and sample allocation is determined using each method for lognormal and Weibull lifetime distributions with both complete and Type 1 right‐censored data under two selected acceleration factor models. The investigations reveal that asymptotic test plans tend to corroborate quite well with exact test plans and thus are suitably robust to small‐sample settings in terms of optimal variance.     

Challenges and new methods for designing reliability experiments

Abstract

Engineers use reliability experiments to determine the factors that drive product reliability, build robust products, and predict reliability under use conditions. This article uses recent testing of a howitzer to illustrate the challenges in designing reliability experiments for complex, repairable systems. We review research in complex system reliability models, failure-time experiments, and experimental design principles. We highlight the need for reliability experiments that account for various intended uses and environments. We leverage lessons learned from current research and propose methods for designing an experiment for a complex, repairable system.     

Order-of-addition experiments: A review and some new thoughts

Abstract

The study of order-of-addition (OofA) experiments is prevalent in many scientific and industrial areas. The statistical design of experiments (DOE) will considerably improve the efficiency of OofA experiments. Designing and modeling the OofA experiments have increasingly received a great deal of attention. In this article, we review the latest work on the design and model of OofA experiments, and introduce some new thoughts. We believe that this article will motivate fruitful applications in real OofA experiments as well as future developments in the methodology.     

Open innovation in Russian state-owned enterprises

ABSTRACT

This paper studies open innovation practices in Russian state-owned enterprises (SOEs). In 2011, the Russian Government set ambitious goals in science, technology and innovation, and uses its large SOEs as channels to achieve these targets. These initiatives focus on the collaboration among innovation actors and introduce open innovation (OI) principles. Based on a large-scale innovation survey, we compare private enterprises to state-owned peers and present selected case studies. Our data support the claim that Russian SOEs are driving the demand for technology and mainly absorb incoming OI activities. Different to their peers, SOEs extend their OI activities to the country’s knowledge producers, such as research and technology organisations (RTOs), and leading universities. They work on incorporating scientific knowledge that could, indeed, hold the key to globally competitive technological innovations, but also have better capabilities to include business partners.

Abbreviation : OI: Open innovation; SOE: State-owned enterprise; RTO: Research and technology organisation; STI: Science, technology and innovation.     

A framework for improving the efficiency of operational testing through Bayesian adaptive design

When developing a product, it is important to consider product performance from a user perspective. This type of evaluation can be done through operational testing—assessing the ability of representative users to satisfactorily accomplish tasks with the product in operationally representative environments. This process can be expensive and time-consuming, but is critical to understanding whether the product can adequately do the job for which it was designed. We show how an existing design of experiments (DOEs) process for operational testing can be leveraged to construct a Bayesian adaptive design. This design, nested within the larger design created by the DOE process, allows interim analyses to stop testing early for success or futility. Representative simulations are presented to demonstrate how these interim analyses can be used in an operational test setting, and reductions in necessary test events are shown. The application of Bayesian-adaptive design methods will allow future operational testing to be conducted in less time and at less expense, on average, without compromising the ability of the existing process to verify the product meets the user's needs.     

Sonic food words influence the experience of beverage healthfulness

The consumption of healthful foods is relevant for the well-being of society. However, understanding healthfulness may be difficult because, in some cultures (i.e., the U.S.), individuals assume that unhealthy equals tasty, an association that does not hold in other contexts (i.e., France). Auditory cues could serve to inform consumers about the expected experience with food and thus could signal the sensory experience of a healthy product. This research contributes to the literature on the use of sound symbolism for analysis of the influence of onomatopoeias as packaging information that influences the expected healthfulness of a bottled drink. The study is a 4 × 4 mixed-model experiment. Grouping was done according to onomatopoeia variables as follows: “Fizz,” “Glup,” “Ahhh,” and control. Beverage color, a within-subject variable, was grouped as green, yellow, red, and control. Results show that the healthful concept is defined in two dimensions: fulfilling and light. Onomatopoeias motivated the experience of a less fulfilling beverage, which had the strongest effect on “Fizz” condition. For the light dimension, “Ahhh” diminishes the perception of light, thus creating the idea that the drink is high in calories. This study reaches out to food industries on the need to find the most consistent and pleasurable sound associated with their products. This will enable food industries to provide information to consumers as well as ascertain how much they enjoy the product.     

The effects of porosity,asphalt content and fiberglass incorporation on the tensile strength and resilient modulus of asphalt concrete blends

Asphalt concrete is the prevailing material used for road surface construction. Its adequate characteristics in providing stability, durability and driving safety are controlled by complex interactions between its components. Thus, it is important to estimate the sensitivity of asphalt concrete mechanical properties as a function of its volumetrics. For this study, different combinations between asphalt content (3.5, 5 and 7.5%) and porosity values (above 4%) were used in order to disassociate these properties. The influence of mixing in fiberglass (0.5%) was also analyzed. It was found that porosity is significantly more relevant than the asphalt content in the prediction of tensile strength and resilient modulus of fiber-free asphalt concretes. In fiber-reinforced mixtures, the mechanical properties are improved by increasing the asphalt content, which suggests a better bonding between fibers and aggregates. For both cases, decreasing porosity is beneficial. By grouping both sets of results, it was possible to create a unique theoretical curve for both the tensile strength (q_t) and the resilient modulus (RM). The RM/q_t ratio was 5800 for the fiber-free group, and 3900 for the fiber-reinforced group - suggesting a better fatigue life indicator for asphalt concretes when fibers are added.     

基于变量决策层的启发式变量选择策略

启发式分支策略是SAT求解器中不可或缺的一部分，直接影响求解器的效率。早期的启发式分支决策需要遍历整个子句数据库，效率比较低。随着独立变量状态衰减和（Variable State Independent Decaying Sum, VSIDS）分支策略的出现，SAT求解器的效率有所提高，但VSIDS策略以及它的延伸策略中变量的增量都只是与变量的冲突次数有关，没有考虑变量的决策层在分支策略中的影响。因此当发生冲突时，如果与冲突有关的变量的得分相同而决策层不同时，对于变量的选择就具有随机性。基于此，本文在阐述变量的决策层的重要性之后在VSIDS策略的基础上，提出一种基于变量决策层的启发式变量选择策略--HSVDL策略。然后通过实例显示HSVDL策略在变量决策阶段选择决策层低的变量的可能性比选择决策层高的变量的可能性要大，而且得分比较小，减少了内存的占用。最后通过实验表明HSVDL策略能够求解出更多的实例，求解器的效率也有所提高，说明该策略有一定的优势。