Approximate TOPSIS for vessel selection under uncertain environment

The selection of appropriate vessels to carry out shipping activities is crucial for many maritime stakeholders including charterers, shipowners, brokers, surveyors and safety engineers. The task is essentially a process of multiple criteria decision making (MCDM) under uncertainty requiring analysts to derive rational decisions from ambiguous and incomplete data contained in different quantitative and qualitative forms. Fuzzy Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) have been well documented in the literature and commonly used in the process of group decision-making under fuzzy environment. While showing the attractiveness in dealing with ambiguous estimates, they have been criticised to be incapable of modelling incompleteness encountered in decision analysis. This paper therefore uses the concept of degrees of belief to develop a novel approximate interval TOPSIS approach for overcoming some of the drawbacks of classical fuzzy TOPSIS methods and facilitating the development of reliable vessel selection models under uncertain environment.     

Shrinkage and model selection with correlated variables via weighted fusion

In this paper, we propose the weighted fusion, a new penalized regression and variable selection method for data with correlated variables. The weighted fusion can potentially incorporate information redundancy among correlated variables for estimation and variable selection. Weighted fusion is also useful when the number of predictors p is larger than the number of observations n. It allows the selection of more than n variables in a motivated way. Real data and simulation examples show that weighted fusion can improve variable selection and prediction accuracy.     

Reliability and validity of an ergonomics-related Job Factors Questionnaire

Musculoskeletal disorders are an important cause of work disability and absenteeism. Specific job factors or tasks may increase the likelihood of developing work-related musculoskeletal disorders. The purpose of the present study was to translate and adapt a Job Factors Questionnaire for the Brazilian–Portuguese language and evaluate its psychometric properties. A cross-cultural adaptation was performed according to an internationally recommended methodology involving translation, synthesis, back-translation, revision by an expert committee, and pre-testing. The psychometric properties were evaluated by administering the questionnaire to 148 employees at two companies involved in the assembly and fabrication of metal products. The reliability of the questionnaire was assessed by measuring the temporal stability through a test–retest design. Construct validity was assessed using the known-groups technique and by comparing workers responses with findings from the Nordic Questionnaire. Reliability was determined to be satisfactory based on Intraclass Correlation Coefficients ranging from 0.54 to 0.73. Construct validity analysis demonstrated a significant difference (p ≤ 0.02) between production and office workers on answers to 10 questionnaire items, and a significant difference (p ≤ 0.01) on the scores of the adapted questionnaire between subjects that indicated presence or absence of musculoskeletal symptoms. The results indicated that the adapted version of the questionnaire had psychometric properties that were acceptable for use in occupational studies involving workers that speak Brazilian–Portuguese.

Relevance to industry

The present study provides results of a cross-cultural adaptation process and a psychometric properties analysis of an instrument that verifies workers' perception of job factors that may lead to work-related pain and discomfort.     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.     

Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.     

The modern paradigm of information science: Informology

This paper considers printed and internet sources determining the content of information science (informology). The philosophical approaches to information (attributive, anthropocentric, and cybernetic) are described, of which only the cybernetic approach is recognized as scientifically grounded. Theoretical and applied informology are distinguished. Statements that can be considered as the axioms and laws of informology, are suggested as the modern paradigm of informology. The existing concepts of informology (probabilistic, semantic, algorithmic, pattern, and qualitative) are described. The general properties of information as well as specific properties of scientific and technical information are determined. The components (divisions), which can be included in the composition of theoretical and applied informology, are described.     

Operating ratio of the technical systems,subjected to failures

The original way of definition of operating ratio in view of reliability of the equipment of the control, time of the control over periodic checks and time of restoration is offered. The received results allow to define the best value of operating ratio of system both in view of, and without taking into account operational expenses.     

Hammerstein Systems Identification in Presence of Hard Nonlinearities of Preload and Dead-Zone Type

Hammerstein system identification is considered in presence of preload and dead zone nonlinearities. The discontinuous feature of these nonlinearities makes it difficult to get a single system parameterization involving linearly all unknown parameters (those of the linear subsystem and those of the nonlinearity). Therefore, system identification has generally been dealt with using multiple stage schemes including different parametrizations and several data acquisition experiences. However, the consistency issue has only been solved under restrictive assumptions regarding the identified system. In this paper, a new identification scheme is designed and shown to be consistent under mild assumptions.     

A heuristic particle swarm optimization method for truss structures with discrete variables

A heuristic particle swarm optimizer (HPSO) algorithm for truss structures with discrete variables is presented based on the standard particle swarm optimizer (PSO) and the harmony search (HS) scheme. The HPSO is tested on several truss structures with discrete variables and is compared with the PSO and the particle swarm optimizer with passive congregation (PSOPC), respectively. The results show that the HPSO is able to accelerate the convergence rate effectively and has the fastest convergence rate among these three algorithms. The research shows the proposed HPSO can be effectively used to solve optimization problems for steel structures with discrete variables.     

The event bush as a semantic-based numerical approach to natural hazard assessment (exemplified by volcanology)

The event bush is a new formalism for organizing knowledge in various fields of geoscience, particularly suitable for hazard assessment purposes. Acting as an intermediary between expert knowledge and the well-established field of Bayesian belief networks, the event bush allows at the same time a variety of other applications, linking geoscientific knowledge to the field of artificial intelligence and uniting probabilistic, deterministic, and fuzzy approaches. In this paper, we present basic principles, mathematical formulation, guidelines for application, and examples, including the connection with Bayesian belief networks. Further development of the method will include spatial and temporal modelling, implementation in mapping in GIS medium, formalization by means of predicate logic, definition of variable states in BBNs by membership functions based on the event bush semantics, and other applications.