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Purpose – The purpose of this study is to develop a numerical framework to predict the time-dependent probability of failure of a bridge subjected to multiple vehicle impacts. Specially, this study focuses on investigating the inter-relationship between changes in life-cycle parameters (e.g., damage size caused by vehicle impact, loss of initial structural capacity, and threshold intervention) and bridges probability of failure.

Design/Methodology/Approach – The numerical procedure using MATLAB program is developed to compute the probability failure of a bridge. First, the importance and characteristics of life-cycle analysis is described. Then, model for damage accumulation and life cycle as a result of heavy vehicle impacts is discussed. Finally, the probability of failure of a bridge subjected to vehicle impacts as a result of change in life-cycle parameters is presented.

Findings – The results of study show that damage size caused by both vehicle impacts and loss of initial structural capacity have a great impact on the long-term safety of bridges. In addition, the probability of failure of a bridge under different threshold limits indicates that the structural intervention (e.g., repair or maintenance) should be undertaken to extend the service life of a bridge.

Research Limitations/Implications – The damage sizes caused by heavy vehicle impacts are based on simple assumptions. It is suggested that there would be a further study to estimate the magnitude of bridge damage as a result of vehicle impact using the full-scale impact test or computational simulation.

Practical Implications – This will allow much better predictions for residual life of bridges which could potentially be used to support decisions on health and maintenance of bridges.

Originality/Value – The life-cycle performance for assessing the time-dependent probability of failure of bridges subjected to multiple vehicle impact has not been fully discussed so far.

The purpose of this chapter is to optimize multi-criteria formulation for green vehicle routing problems by mixed integer programming. This research is about the road freight transportation of a Spanish company of groceries. This company has more power in the north of Spain and hence it was founded there. The data used for the computational experiments are focused in the northern region of Spain. The data have been used to decide the best route in order to obtain a minimization of costs for the company. The problem focused on the distance traveled and the altitude difference; by studying these parameters, the best solution of route transportation has been made. The software used to solve this model is CPLEX solver with AMPL programming language. This has been helpful to obtain the results for the research and some conclusions have been obtained from them.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

This chapter describes the efforts of a team of health care workers to make a sub-acute health care facility (SCF) serving profoundly damaged children into a high reliability organization (HRO). To obtain this goal, the health care team implemented change in four behavioral areas: (1) risk awareness and acknowledgment; (2) defining care; (3) how to think and make decisions; and (4) information flow. The team focused on five reliability enhancement issues that emerged from previous research on banking institutions: (1) process auditing; (2) the reward system; (3) quality degradation; (4) risk awareness and acknowledgment; and (5) command and control. These HRO processes emerged from the change effort. Three additional HRO processes also emerged: high trust, and building a high reliability culture based on values and on beliefs. This case demonstrates that HRO processes can reduce costs, improve safety, and aid in developing new markets. Other experiences in implementing high reliability processes show that each organization must tailor make processes to its own situation (e.g. BP, U.S. Chemical Safety and Hazards Board, Federal Aviation Administration, U.S. Navy Aviation Program, and Kaiser Permanente Health Care System). Just as in the flexibility called for in organizing for high reliability operations, flexibility is called for in deciding which HRO processes work in specific situations.

This paper studies organizational change following a shift in an industry environment, in the context of how a focused factory adapts to a change in its manufacturing objectives. We use the organizational nature of production operations to suggest that the effectiveness of adaptation will depend on how well the manufacturing requirements of the new objectives match manufacturing capabilities at the production line level. We test our hypotheses using primary data from the Hartselle, Alabama compressor manufacturing focused factory of the Copeland Corporation. The results suggest that factors that influence adaptability derive from individual and organizational competence, and that the direction and extent of their influence depends on the systemic nature of the operational activity concerned. The results highlight roles of carefully designed complexity in operations and of process-oriented decision making on the shop floor in successful adaptation. This work contributes to our understanding of how business organizations overcome constraints to change.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.