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This study addresses pediatrician perceptions of a telemedicine program as it developed from 1998 to 2000. The researchers completed structured interviews with ten pediatricians who provided telemedicine services between a university medical center and an urban school district. The results describe how pediatricians understood the telemedicine program, including technology, consult process, and relationships. This understanding of how pediatricians “make sense” of telemedicine allows optimal planning for the program's future and may inform other telemedicine initiatives about challenges in the pediatric setting.

There is a great incentive for developing systematic approaches that effectively identify strategies for planning oilfield complexes. This paper proposes an MILP that relies on a reformulation of the model developed by Tsarbopoulou (UCL M.S. Dissertation, London, 2000). Moreover, a bilevel decomposition technique is applied to the MILP. A master problem determines the assignment of platforms to wells and a planning subproblem calculates the timing for fixed assignments. Furthermore, a heuristic search procedure that relies on the distance between platforms and wells is applied in order to reduce the search region. Results show that the decomposition approach using heuristic generates optimal solutions for instances of up to 500 wells and 25 platforms in 10 discrete time periods that otherwise could not be solved with a full-scale approach. One important feature regarding these instances is that they correspond to problems of real-world dimension.

An optimal operation planning of a production process with a buffer and an electric power plant has been considered. The problem is formulated as a mixed-integer linear program with special structure. A decomposition algorithm has been proposed for solving the problem easily by using a process computer. According to the numerical results, the proposed algorithm is expected to be applicable to real situation such as real time control and planning with use of a process computer.

An optimal planning model of distribution network with loops which combines optimal network structure and optimal allocation of sectionalizing and loop switches is presented. By minimizing the total expense of investment cost, power loss expense and punition expense for power cut, The power supply economy and reliability of distribution network are considered simultaneously. We have the chateaus represent the electrical source and load. And four different paths represent the possible connection situation between two chateaux. Ant Colony Algorithm(ACA) is used to find out the optimal solution. The simulation result indicates that ACA can solve the optimal planning problem of distribution network with loops. (6 pages)

The problem of domain-independent automated planning has been a topic of research in Artificial Intelligence since the very beginnings of the field. Due to the desire not to rely on vast quantities of problem specific knowledge, the most widely adopted approach to automated planning is search. The topic of this thesis is the development of methods for achieving effective search control for domain-independent optimal planning through the construction of admissible heuristics. The particular planning problem considered is the so called “classical” AI planning problem, which makes several restricting assumptions. Optimality with respect to two measures of plan cost are considered: in planning with additive cost, the cost of a plan is the sum of the costs of the actions that make up the plan, which are assumed independent, while in planning with time, the cost of a plan is the total execution time – makespan – of the plan. The makespan optimization objective can not, in general, be formulated as a sum of independent action costs and therefore necessitates a problem model slightly different from the classical one. A further small extension to the classical model is made with the introduction of two forms of capacitated resources. Heuristics are developed mainly for regression planning, but based on principles general enough that heuristics for other planning search spaces can be derived on the same basis. The thesis describes a collection of methods, including the hm, additive hm and improved pattern database heuristics, and the relaxed search and boosting techniques for improving heuristics through limited search, and presents two extended experimental analyses of the developed methods, one comparing heuristics for planning with additive cost and the other concerning the relaxed search technique in the context of planning with time, aimed at discovering the characteristics of problem domains that determine the relative effectiveness of the compared methods. Results indicate that some plausible such characteristics have been found, but are not entirely conclusive.

A simulation optimization method is presented to realize the optimal planning on the gate system on container terminals. At first, the formulation of mathematical programming model is established including the planning objectives and constraints according to the analysis on the operation requirement of the gate system. The optimal objective is to minimize the total cost of construction and ensure the desired operation efficiency. Then, considering the uncertain and stochastic activities in the system, the discrete-event system simulation model is built. To solve the optimal planning problem, the requirement for optimization algorithm suit for the simulation model is discussed and the approach of simulation optimization is presented. The optimization method is presented that combines genetic algorithm with the discrete-event system simulation model of the gate system. At last, an actual case is analyzed to illustrate the validity and effectiveness. The results from simulation optimization method are compared with traditional planning method and the advantage of this method is shown. Moreover, the sensitivity of this planning result is analyzed.

A multiperiod Mixed Integer Nonlinear Programming (MINLP) model for offshore oilfield infrastructure planning is presented where nonlinear reservoir behavior is incorporated directly into the formulation. Discrete decisions include the selection of production platforms, well platforms and wells to be installed/drilled, as well as the drilling schedule for the wells over the planning horizon. Continuous decisions include the capacities of the platforms, as well as the production profile for each well in each time period.

We show in this article how the Weighted CSP framework can be used to solve an optimisation version of numerical planning. The WCSP finds an optimal plan in the planning graph containing all solution plans of minimum length. Experimental trials were performed to study the impact of soft arc consistency techniques (FDAC and EDAC) on the efficiency of the search for an optimal plan in this graph. We conclude by giving a possible theoretical explanation for the fact that we were able to solve optimisation problems involving several hundred variables.

A risk-based inspection system and a piping inspection guideline model were developed in this study. The research procedure consists of two parts--the building of a risk-based inspection model for piping and the construction of a risk-based piping inspection guideline model. Field visits at the plant were conducted to develop the risk-based inspection and strategic analysis system. A knowledge-based model had been built in accordance with international standards and local government regulations, and the rational unified process was applied for reducing the discrepancy in the development of the models. The models had been designed to analyze damage factors, damage models, and potential damage positions of piping in the petrochemical plants. The purpose of this study was to provide inspection-related personnel with the optimal planning tools for piping inspections, hence, to enable effective predictions of potential piping risks and to enhance the better degree of safety in plant operations that the petrochemical industries can be expected to achieve. A risk analysis was conducted on the piping system of a petrochemical plant. The outcome indicated that most of the risks resulted from a small number of pipelines.

One of the main obstacles to the diffusion of the distributed generation (DG) is the actual distribution system structure, that was not built to allocate a large amount of generation. However, many technical and political drives are urging forward a massive penetration of DG, which will ineluctably guide to a radical transformation of the MV distribution networks. One of the changes could be the adoption of a meshed operation. For this reason, in the paper a new optimization algorithm based on heuristic techniques has been developed and implemented in an efficient software package, in order to find the more suitable meshed network arrangement. Moreover, some comparisons with the radial operation are reported to show the potential benefits of changing the operation philosophy in presence of a massive penetration of DG.

The developed system involves: selection of optimal hubs and delineation of their influence areas; estimation of demand; and generation of optimal paths and service frequencies. Fuzzy clustering and Self-organizing-map methods aggregate the stops into a number of clusters. A hub is located with the objective to minimize the ‘Total Travel Distance’ within a cluster. Optimal set of clusters is one that provides the minimum ‘Total Passenger Time’ for the network. Routing model generates reasonably direct routes with high frequency. Optimal path is selected on the basis of maximum ‘Desire passenger-km per km’. Number of trips to be operated for a route depends upon the demand served along the route and the passenger flow on various links of the route. To estimate the optimal trips for a route, an iterative heuristic algorithm is adopted in the scheduling model. The devised methodology is successfully implemented for New Delhi, the capital city of India. The total daily transit demand generated at 1542 stops is 7.67 million passengers. A set of fifty optimal hubs is identified and 181 inter hub routes are generated. Eighty-eight of these inter-hub routes, which have very high demand, need to be operated with automated transit vehicles (APM). A total of 305 secondary routes (intra-hub) are also generated. Optimal scheduling is done for all the 486 transit routes. For peak period, a total fleet of 11497 standard size buses is required at the desired level of service.

Optimal planning of cellular networks is one of the most fundamental problems in network design. This paper discusses cell planning problems for the fourth generation (4G) cellular networks. We describe important planning aspects derived by the anticipated 4G technologies and model several relevant cell planning problems. We then review several algorithmic techniques for solving these problems.

Methods for solving cluster-optimal problems are presented for both minimum time and minimum fuel tranfers near an elliptical reference orbit. The solutions rely on a linearized approximation of the relative orbital dynamics and use a spline approximation to determine the effects of thrust inputs. An extendable parameterization technique is also outlined for formations and formation transits. Examples of both centered and non-centered formations are solved, with focus on application to the tetrahedron specified for the Magnetospheric Multiscale mission.

This paper presents a new possibilistic (fuzzy) model for the multiobjective optimal planning of power distribution networks that finds out the nondominated multiobjective solutions corresponding to the simultaneous optimization of the fuzzy economic cost, level of fuzzy reliability, and exposure (optimization of robustness) of such networks, using an original and powerful meta-heuristic algorithm based on Tabu Search. This model determines the optimal location and size of the future feeders and substations in distribution networks with dimensions significantly larger than the ones usually presented in papers on the matter. The model also allows to determine the optimal reserve feeders (location and size) that provide the best distribution network reliability at the lowest cost for a given level of robustness (exposure). The model and the algorithm have been intensively tested in real distribution networks, which proves their practical application to large power distribution systems. © 2004 IEEE.

The geographic information systems (GIS) platform is used in spatial load forecasting (SLF) and the mathematical models of the substation location and capacity optimisation problems are established in this paper. Based on the theory of network flow, a new multi-period optimal selecting algorithm of substation is proposed, which could determine the reasonable location, capacity and time that are put into the running of the substation. The real instance shows that this algorithm could solve the multi period optimal selecting problem of substations in distribution system planning (DSP) successfully, and has a practical value.

Radiotherapy is a critical component of treatment for many patients with cervical cancer. The role of concurrent cisplatin-based chemotherapy in the majority of cases where radiotherapy is indicated has been established. However, optimal planning and delivery of radiotherapy require attention to multiple factors beyond combined-modality chemoradiation and the continuing search for novel and effective synergistic systemic agents. Several important issues surrounding radiotherapy for cervical cancer that require clarification include the following: the effect of anemia and tumor hypoxia on outcome and their potential as therapeutic targets, the appropriate incorporation of contemporary imaging and high-technology treatment planning systems in routine clinical practice, the role of prophylactic para-aortic radiation, and the role of radioprotectors. Ongoing and newly proposed studies are expected to provide insights into these questions, which will ultimately lead to enhanced radiotherapeutic and overall care for patients with cervical cancer.

Operable sensing is studied as a means for improving system performance. Both single and sequential planning are analysed, and the complexity due to risk-averseness in various formulations discussed. Three classes of sensing operation are defined and analysed. publishedVersion

A new method is presented in this paper to solve the optimal planning problem of distribution substations. The procedure proposed doesn't require candidate substation locations and can automatically select the optimal sizes and locations of substations in power distribution systems. An effective solution algorithm is also presented. >

In this article, techniques developed in the science of genetic computing are applied to solve the problem of optimally selecting robot measurement configurations, which is an important element in successfully completing a robot calibration experiment. Genetic algorithms are customized for a type of robot measurement configuration selection problem in which the robot workspace constraints are defined in terms of robot joint limits. Simulation studies are conducted to examine the effectiveness of the genetic algorithms for the application. ©1997 John Wiley & Sons, Inc.

The structure and methodological features of a new optimal planning and dynamic scheduling system for a total plant continuous manufacturing process is introduced. A hybrid Petri net, a combination of a timed continuous Petri net and extended Petri net, is developed to model the process together with static equipment models and expert knowledge. Definitions of the system components and model construction steps are discussed, while a simplified example is also presented.

The paper proposes a new approach-a grey fuzzy multiobjective mixed integer programming (GFMOMIP) model-for the evaluation of sustainable management strategies of solid waste management in a metropolitan region. In particular, it demonstrates how uncertain messages can be quantified by specific membership functions and combined through the use of grey numbers in a multiobjective solid waste management framework. It shows that the grey fuzzy outputs can successfully reflect system complexity and generate more flexible management strategies.

A scheme using the Tabu search is proposed for optimal planning of dynamic voltage restorer (DVR) on a distribution system. The proposed scheme is posed as a multiobjective optimization problem for maximizing a fuzzy performance index, which represents the cost expenditure of installed DVR, voltage sag enhancement on sensitive loads and overall voltage improvement in the distribution network.

The objective of this paper is to study the behaviour of the landfill soil-to-refuse (S/R) ratio when size, geometry and operating parameters of the daily cell vary over realistic ranges. A simple procedure is presented (1) for calculating the cell parameters values which minimise the S/R ratio and (2) for studying the sensitivity of this minimum S/R ratio to variations in cell size, final refuse density, working face length, lift height and cover thickness. In countries where daily soil cover is required, savings in landfill space could be realised following this procedure. The sensitivity of minimum S/R to variations in cell dimensions decreases with cell size. Working face length and lift height affect the S/R ratio significantly. This procedure also offers the engineer an additional tool for comparing one large daily cell with two or more smaller ones, at two different working faces within the same landfill.

The problems of optimization models construction and algorithms of strategic planning of production sales volumes for single-stage stochastic manufacturing systems are considered. The problems of practical application of the offered approach to the goods strategy development within the framework of the computer system of decision making support for want of strategic planning of marketing for manufacturing of electronic engineering are considered.

The Environmental Systems Research Candidates (ESRC) Program, which is scheduled to end September 2001, was established in April 2000 as part of the Environmental Systems Research and Analysis Program at the Idaho National Engineering and Environmental Laboratory (INEEL) to provide key science and technology to meet the clean-up mission of the U.S. Department of Energy Office of Environmental Management, and perform research and development that will help solve current legacy problems and enhance the INEEL’s scientific and technical capability for solving longer-term challenges. This report documents the progress and accomplishments of the ESRC Program from April through September 2000. The ESRC Program consists of 24 tasks subdivided within four research areas: A. Environmental Characterization Science and Technology. This research explores new data acquisition, processing, and interpretation methods that support cleanup and long-term stewardship decisions. B. Subsurface Understanding. This research expands understanding of the biology, chemistry, physics, hydrology, and geology needed to improve models of contamination problems in the earth’s subsurface. C. Environmental Computational Modeling. This research develops INEEL computing capability for modeling subsurface contaminants and contaminated facilities. D. Environmental Systems Science and Technology. This research explores novel processes to treat waste and decontaminate facilities. Our accomplishments during FY 2000 includemore » the following: • We determined, through analysis of samples taken in and around the INEEL site, that mercury emissions from the INEEL calciner have not raised regional off-INEEL mercury contamination levels above normal background. • We have initially demonstrated the use of x-ray fluorescence to image uranium and heavy metal concentrations in soil samples. • We increased our understanding of the subsurface environment; applying mathematical complexity theory to the problem of transport of subsurface contaminants. • We upgraded the INEEL’s high-speed computer link to offsite supercomputers from T1 (1.5 MB/s) to DS3 (45 MB/s). Procurements have initiated a further upgrade to OC3 (155 MB/s) with additional onsite computational power that should put the INEEL on the Top 500 Supercomputing Sites list. • We developed advanced decontamination, decommissioning, and dismantlement techniques, including the Decontamination, Decommissioning, and Remediation Optimal Planning System.« less

No consensus has yet been reached about the “correct” method for determining information-relevant partial cost variances. As shown below, the problem of choosing a suitable method is complicated by the fact that even optimal planning under certainty cannot preclude actual values from being below standard values. This implies that, in contrast to the conventional view, intensity (production rate) variances resulting from an actual-vs-standard comparison can be negative. It is shown that in order to reveal intensity variances caused by inefficient behavior, it is necessary to distinguish between optimum, standard, and actual intensities, and therefore to integrate the theory of adaptation forms developed by Gutenberg into cost control. Methods commonly proposed for practical application are analyzed with regard to the extent to which they result in first order partial variances (particularly intensity variances) which comprise concealed, information-distorting variances of higher orders as compensatory amounts. In order to avoid the occurence of compensatory effects, a method based on minimum values is proposed, which, for all data constellations, leads to unambiguous intensity variances indicating possible cost reductions with respect to standard cost.

The key aspects of optimal modernization of mobile communication systems are analyzed. The problem is shown to be reduced to the basic problem of optimal planning of such systems.

This paper presents a framework for optimal planning and replanning of disassembly processes. Planning is formulated as a graph search where the graph consists of all the feasible disassembly sequences. The process of re-planning is based on adaptation of the original plan whenever new evidences on the product condition are discovered or new goals are considered. Adaptation scheme uses dependencies among product’s components to propagate uncertainty regarding their condition as sensed during the disassembly process. Using the proposed framework we present a simple algorithm for efficient remanufacturing of product.

A genetic algorithm based optimization method is proposed for the planning problem of energy plant configurations. In such a planning problem, a plant configuration, i.e., types, models, and numbers of equipment, is determined so as to satisfy required energy demand conditions and to minimize the sum of plant facility cost and input energy cost. This is a combinatorial optimization problem similar to the knapsack problem, which is hard to find an optimal configuration for due to the huge number of alternatives. In this paper, we apply a genetic algorithm to such an optimal planning problem by representing a plant configuration with bit vectors and by arranging cost functions so as to keep search performance superior against the deceptive problem. The method is implemented on a symmetric shared-memory, multi-CPU workstation, where almost linear speedup is accomplished. Its performance is demonstrated by computational examples of a cogeneration plant and comparison results with a random search and a simulated annealing method.

This paper, is concerned with the evaluation of economic and energy saving characteristics of a super waste incineration cogeneration plant, which is equipped with gas turbines as topping cycle to overcome a drawback of low power generating efficiency of conventional waste incineration cogeneration plants only with steam turbines. Economic and energy saving characteristics are evaluated using an optimal planning method which determines capacities and operational strategies of constituent equipment from their many alternatives so as to minimize the annual total cost. Through a case study, advantages of a super waste incineration cogeneration plant are shown in comparison with a conventional one. A parametric study is also carried out with respect to the amounts of waste collected and energy distributed.Copyright © 1996 by ASME

In this paper we study the Graph Motion Planning of 1 Robot problem (GMP1R) on a tree. This problem consists in computing a minimum cost plan for moving a robot from one vertex to another in a tree whose vertices can have movable obstacles.

Compiling a geomagnetic map is the final stage of magnetic surveys. The connection between the technique of the survey, its accuracy and the map quality is clear. The map quality is determined by the accuracy of the information taken from it. The accuracy of the map characterizes by its rms (rE); summarizing from the rms of the initial information and from the errors of mapping:© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.