The goal of this work is the development of a black-box solver based on the scatter search methodology. In particular, we seek a solver capable of obtaining high quality outcomes to optimization problems for which solutions are represented as a vector of integer values. We refer to these problems as integer optimization problems. We assume that the decision variables are bounded and that there may be constraints that require that the black-box evaluator is called in order to know whether they are satisfied. Problems of this type are common in operational research areas of applications such as telecommunications, project management, engineering design and the like.Our experimental testing includes 171 instances within four classes of problems taken from the literature. The experiments compare the performance of the proposed method with both the best context-specific procedures designed for each class of problem as well as context-independent commercial software. The experiments show that the proposed solution method competes well against commercial software and that can be competitive with specialized procedures in some problem classes.

We analyse the point availability of a repairable duplex system characterized by cold standby and by a priority rule. The system is attended by two (general) heterogeneous repairmen. To describe the random behaviour of the system, we introduce a stochastic process endowed with probability measures satisfying (coupled) partial differential equations. The solution procedure is based on the theory of sectionally holomorphic functions combined with the notion of dual transforms. The unique solution of the equations determines the point availability of the system. Computational results for the point availability are derived by a numerical solution of an appropriate integral equation.

My analysis focuses on two main observations. First, many competing schools of thoughts are currently present in economics with no predominant paradigm. We are experiencing an era of pluralism (Davis J Econ Methodol 14(3):275–290, 2007, Camb J Econ 32:249–366, 2008; Colander 2000; Colander et al. J Polit Econ 16(4):485–499, 2004). The term ‘pluralism’ is extremely interesting since, as I will show, it has different dimensions to it. These offer insights into interpreting the tangled universe of the economics. Second, there is a progressive intertwining of innovation economics with complexity economics, which I argue provides an instance of the above-described shift toward pluralism.

Public expertise in safety, security and environment (SSE) is a process that is increasingly submitted to control and transparency. As decision-making, the exercise of expertise involves subjectivity and judgment. An oversight, a monitoring and an aiding approach is therefore required for its conduct and its governance. This paper proposes a novel way of embedding ethical aspects and participative decision-making elements into the process of risk assessment and risks management. Based on their experience feedback, the authors first propose some early contributions to study the validity and the legitimacy of expertise in SSE. In the second part of the paper, the authors give an overview on how public expertise is organized in France and how the problems and the conclusions are framed in SSE. Finally, the authors propose a generic integrated framework for public expertise that constitutes the “responsible exercise of expertise”. This framework allows framing a valid and a legitimate expertise process and its conclusions.

Successfully developing new products is critical to an entrepreneurial firm’s continued success. Based on the resource management model, this study aims to answer the key research question: how entrepreneurial firms leverage network competence and technological capability to enhance their new product development (NPD) performance in a turbulent environment. Using data collected from 134 entrepreneurial firms in China, we investigate the performance effects of network competence and technological capability, and the moderating effects of technological turbulence and market turbulence. Our findings show that network competence has a positive impact on NPD performance and technological capability plays a mediating role between network competence and NPD performance. Technological turbulence enhances the performance effects of network competence and technological capability; market turbulence advances the performance effect of network competence, but fails to exert significant negative impact on that of technological capability. We discuss managerial implications of our findings and offer directions for future research.

We examine insider trading around open-market share repurchases and find that insiders trade passively in 3 months prior to repurchase announcements and in up to 12 months following the announcements. Furthermore, both pre-announcement and post-announcement abnormal insider trading is unrelated to short-term announcement returns but correlated with long-term post-announcement returns. Our results indicate that corporate insiders trade passively around repurchase announcements in accordance with their perceived undervaluation to exploit the long-run abnormal stock returns related to the events.

Testing is often cited as one of the most costly operations in testing dependable systems (Heimdahl et al. 2001). A particular challenging task in testing is test-case generation. To improve the efficiency of test-case generation and reduce its cost, recently automated formal verification techniques such as model checking are extended to automate test-case generation processes. In model-checking-assisted test-case generation, a test criterion is formulated as temporal logical formulae, which are used by a model checker to generate test cases satisfying the test criterion. Traditional test criteria such as branch coverage criterion and newer temporal-logic-inspired criteria such as property coverage criteria (Tan et al. 2004) are used with model-checking-assisted test generation. Two key questions in model-checking-assisted test generation are how efficiently a model checker may generate test suites for these criteria and how effective these test suites are. To answer these questions, we developed a unified framework for evaluating (1) the effectiveness of the test criteria used with model-checking-assisted test-case generation and (2) the efficiency of test-case generation for these criteria. The benefits of this work are three-fold: first, the computational study carried out in this work provides some measurements of the effectiveness and efficiency of various test criteria used with model-checking-assisted test case generation. These performance measurements are important factors to consider when a practitioner selects appropriate test criteria for an application of model-checking-assisted test generation. Second, we propose a unified test generation framework based on generalized Büchi automata. The framework uses the same model checker, in this case, SPIN model checker (Holzmann 1997), to generate test cases for different criteria and compare them on a consistent basis. Last but not least, we describe in great details the methodology and automated test generation environment that we developed on the basis of our unified framework. Such details would be of interest to researchers and practitioners who want to use and extend this unified framework and its accompanying tools.

This paper studies a scheduling control problem for a single-server multiclass queueing network in heavy traffic, operating in a changing environment. The changing environment is modeled as a finite-state Markov process that modulates the arrival and service rates in the system. Various cases are considered: fast changing environment, fixed environment, and slowly changing environment. In all cases, the arrival rates are environment dependent, whereas the service rates are environment dependent when the environment Markov process is changing fast, and are assumed to be constant in the other two cases. In each of the cases, using weak convergence analysis, in particular functional limit theorems for Poisson processes and ergodic Markov processes, it is shown that an appropriate “averaged” version of the classical $$c\mu $$ -policy (the priority policy that favors classes with higher values of the product of holding cost $$c$$ and service rate $$\mu $$ ) is asymptotically optimal for an infinite horizon discounted cost criterion.

Uncertainty has an almost negligible impact on project value in the standard economic model. I show that a comprehensive evaluation of uncertainty and uncertainty attitude changes this picture fundamentally. The illustration of this result relies on the discount rate, which is the crucial determinant in balancing immediate costs against future benefits, and the single most important determinant of optimal mitigation policies in the integrated assessment of climate change. First, the paper removes an implicit assumption of (intertemporal or intrinsic) risk neutrality from the standard economic model. Second, the paper introduces aversion to non-risk uncertainty (ambiguity). I show a close formal similarity between the model of intertemporal risk aversion, which is a reformulation of the widespread Epstein–Zin–Weil model, and a recent model of smooth ambiguity aversion. I merge the models, achieving a threefold disentanglement between risk aversion, ambiguity aversion, and the propensity to smooth consumption over time.