16,454 research outputs found
Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS
We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making
Intelligent systems in manufacturing: current developments and future prospects
Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS
A two-stage dynamic model on allocation of construction facilities with genetic algorithm
Author name used in this publication: K. W. Chau2003-2004 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe
A two-stage dynamic model on allocation of construction facilities with genetic algorithm
By their very nature, activities within the construction site are generally highly dynamic and complex. Hence, it is highly desirable to be able to formulate the optimal strategy for allocating site-level facilities at different times of the project. The principal objective is to minimize the total cost, which comprises the transportation, handling, capital, and operating costs at potential intermediate transfer centers of various plant and material resources over the entire project duration. The problem can be formulated as a mixed integer program, which entails enormous computational effort for the solution, in particular when the problem size is large. In this paper, a two-stage dynamic model is developed to assist construction planners to formulate the optimal strategy for establishing potential intermediate transfer centers for site-level facilities such as batch plants, lay-down yards, receiving warehouses, various workshops, etc. Under this approach, the solution of the problem is split into two stages, namely, a lower-level stage and an upper-level stage. The former can be solved by a standard linear programming method, whereas the latter is solved by a genetic algorithm. The efficiency of the proposed algorithm is demonstrated through case examples.Department of Civil and Environmental EngineeringAuthor name used in this publication: K. W. Cha
Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies
Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin
Construction safety and digital design: a review
As digital technologies become widely used in designing buildings and infrastructure, questions arise about
their impacts on construction safety. This review explores relationships between construction safety and
digital design practices with the aim of fostering and directing further research. It surveys state-of-the-art
research on databases, virtual reality, geographic information systems, 4D CAD, building information
modeling and sensing technologies, finding various digital tools for addressing safety issues in the
construction phase, but few tools to support design for construction safety. It also considers a literature on
safety critical, digital and design practices that raises a general concern about ‘mindlessness’ in the use of
technologies, and has implications for the emerging research agenda around construction safety and digital
design. Bringing these strands of literature together suggests new kinds of interventions, such as the
development of tools and processes for using digital models to promote mindfulness through multi-party
collaboration on safet
Genetic algorithm optimization for dynamic construction site layout planning
The dynamic construction site layout planning
(DCSLP) problem refers to the efficient placement and relocation
of temporary construction facilities within a dynamically
changing construction site environment considering
the characteristics of facilities and work interrelationships,
the shape and topography of the construction site, and the
time-varying project needs. A multi-objective dynamic optimization
model is developed for this problem that considers
construction and relocation costs of facilities, transportation
costs of resources moving from one facility to another or to
workplaces, as well as safety and environmental considerations
resulting from facilities’ operations and interconnections.
The latter considerations are taken into account in
the form of preferences or constraints regarding the proximity
or remoteness of particular facilities to other facilities
or work areas. The analysis of multiple project phases and
the dynamic facility relocation from phase to phase highly
increases the problem size, which, even in its static form,
falls within the NP (for Nondeterministic Polynomial time)-
hard class of combinatorial optimization problems. For this
reason, a genetic algorithm has been implemented for the
solution due to its capability to robustly search within a large
solution space. Several case studies and operational scenarios
have been implemented through the Palisade’s Evolver
software for model testing and evaluation. The results indicate
satisfactory model response to time-varying input data
in terms of solution quality and computation time. The model
can provide decision support to site managers, allowing
them to examine alternative scenarios and fine-tune optimal
solutions according to their experience by introducing desirable
preferences or constraints in the decision process
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