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PubMed2002

An optimisation model for regional integrated solid waste management I. Model formulation.

Increased environmental concerns and the emphasis on material and energy recovery are gradually changing the orientation of MSW management and planning. In this context, the application of optimisation techniques have been introduced to design the least cost solid waste management systems, considering the variety of management processes. This study presents a model that was developed and applied to serve as a solid waste decision support system for MSW management taking into account both socio-economic and environmental considerations. The model accounts for solid waste generation rates, composition, collection, treatment, disposal as well as potential environmental impacts of various MSW management techniques. The model follows a linear programming formulation with the framework of dynamic optimisation. The model can serve as a tool to evaluate various MSW management alternatives and obtain the optimal combination of technologies for the handling, treatment and disposal of MSW in an economic and environmentally sustainable way. The sensitivity of various waste management policies will be also addressed. The work is presented in a series of two papers: (I) model formulation, and (II) model application and sensitivity analysis.

Conservation of Natural Resources↗

PubMed2002

An optimisation model for regional integrated solid waste management II. Model application and sensitivity analyses.

Increased environmental concerns and the emphasis on material and energy recovery are gradually changing the orientation of MSW management and planning. In this context, the application of optimisation techniques have been introduced to design the least cost solid waste management systems, considering the variety of management processes (recycling, composting, anaerobic digestion, incineration, and landfilling), and the existence of uncertainties associated with the number of system components and their interrelations. This study presents a model that was developed and applied to serve as a solid waste decision support system for MSW management taking into account both socio-economic and environmental considerations. The model accounts for solid waste generation rates, composition, collection, treatment, disposal as well as potential environmental impacts of various MSW management techniques. The model follows a linear programming formulation with the framework of dynamic optimisation. The model can serve as a tool to evaluate various MSW management alternatives and obtain the optimal combination of technologies for the handling, treatment and disposal of MSW in an economic and environmentally sustainable way. The sensitivity of various waste management policies is also addressed. The work is presented in a series of two papers: (I) model formulation, and (II) model application and sensitivity analysis.

Conservation of Natural Resources↗

PubMed2004

A model to minimize joint total costs for industrial waste producers and waste management companies.

The model LINKopt is a mixed-integer, linear programming model for mid- and long-term planning of waste management options on an inter-company level. There has been a large increase in the transportation of waste material in Germany, which has been attributed to the implementation of the European Directive 75/442/EEC on waste. Similar situations are expected to emerge in other European countries. The model LINKopt has been developed to determine a waste management system with minimal decision-relevant costs considering transportation, handling, storage and treatment of waste materials. The model can serve as a tool to evaluate various waste management strategies and to obtain the optimal combination of investment options. In addition to costs, ecological aspects are considered by determining the total mileage associated with the waste management system. The model has been applied to a German case study evaluating different investment options for a co-operation between Daimler-Chrysler AG at Rastatt, its suppliers, and the waste management company SITA P+R GmbH. The results show that the installation of waste management facilities at the premises of the waste producer would lead to significant reductions in costs and transportation.

Decision Making, Organizational↗

PubMed1990

Managing physician efficiency and effectiveness in providing hospital services.

Physicians control more than 80 percent of the decisions affecting health costs. Consequently, managing physician practice patterns is an important avenue to reducing health care costs. One approach to identifying inefficient practice patterns is demonstrated in this pilot study of physicians treating heart shock patients. Physicians are evaluated using data envelopment analysis (DEA), a relatively new linear-program-based efficiency evaluation tool. This approach (1) locates physicians using excess resources in treating patients, (2) estimates the amount of excess resources used, and (3) explicitly considers the quality of patient care in the overall assessment of the physician's practice patterns. Findings of physician inefficiency that are stable over time could be used to alter practice patterns and subsequently to assist in cost containment.

Data Collection↗

PubMed2005

Selecting additional tag SNPs for tolerating missing data in genotyping.

BACKGROUND: Recent studies have shown that the patterns of linkage disequilibrium observed in human populations have a block-like structure, and a small subset of SNPs (called tag SNPs) is sufficient to distinguish each pair of haplotype patterns in the block. In reality, some tag SNPs may be missing, and we may fail to distinguish two distinct haplotypes due to the ambiguity caused by missing data. RESULTS: We show there exists a subset of SNPs (referred to as robust tag SNPs) which can still distinguish all distinct haplotypes even when some SNPs are missing. The problem of finding minimum robust tag SNPs is shown to be NP-hard. To find robust tag SNPs efficiently, we propose two greedy algorithms and one linear programming relaxation algorithm. The experimental results indicate that (1) the solutions found by these algorithms are quite close to the optimal solution; (2) the genotyping cost saved by using tag SNPs can be as high as 80%; and (3) genotyping additional tag SNPs for tolerating missing data is still cost-effective. CONCLUSION: Genotyping robust tag SNPs is more practical than just genotyping the minimum tag SNPs if we can not avoid the occurrence of missing data. Our theoretical analysis and experimental results show that the performance of our algorithms is not only efficient but the solution found is also close to the optimal solution.

Algorithms↗

PubMed2006

SNA--a toolbox for the stoichiometric analysis of metabolic networks.

BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

Algorithms↗

PubMed2005

Prediction of MHC class II binding peptides based on an iterative learning model.

BACKGROUND: Prediction of the binding ability of antigen peptides to major histocompatibility complex (MHC) class II molecules is important in vaccine development. The variable length of each binding peptide complicates this prediction. Motivated by a text mining model designed for building a classifier from labeled and unlabeled examples, we have developed an iterative supervised learning model for the prediction of MHC class II binding peptides. RESULTS: A linear programming (LP) model was employed for the learning task at each iteration, since it is fast and can re-optimize the previous classifier when the training sets are altered. The performance of the new model has been evaluated with benchmark datasets. The outcome demonstrates that the model achieves an accuracy of prediction that is competitive compared to the advanced predictors (the Gibbs sampler and TEPITOPE). The average areas under the ROC curve obtained from one variant of our model are 0.753 and 0.715 for the original and homology reduced benchmark sets, respectively. The corresponding values are respectively 0.744 and 0.673 for the Gibbs sampler and 0.702 and 0.667 for TEPITOPE. CONCLUSION: The iterative learning procedure appears to be effective in prediction of MHC class II binders. It offers an alternative approach to this important prediction problem.

Journal Article↗

PubMed2006

A combinatorial optimization approach for diverse motif finding applications.

BACKGROUND: Discovering approximately repeated patterns, or motifs, in biological sequences is an important and widely-studied problem in computational molecular biology. Most frequently, motif finding applications arise when identifying shared regulatory signals within DNA sequences or shared functional and structural elements within protein sequences. Due to the diversity of contexts in which motif finding is applied, several variations of the problem are commonly studied. RESULTS: We introduce a versatile combinatorial optimization framework for motif finding that couples graph pruning techniques with a novel integer linear programming formulation. Our approach is flexible and robust enough to model several variants of the motif finding problem, including those incorporating substitution matrices and phylogenetic distances. Additionally, we give an approach for determining statistical significance of uncovered motifs. In testing on numerous DNA and protein datasets, we demonstrate that our approach typically identifies statistically significant motifs corresponding to either known motifs or other motifs of high conservation. Moreover, in most cases, our approach finds provably optimal solutions to the underlying optimization problem. CONCLUSION: Our results demonstrate that a combined graph theoretic and mathematical programming approach can be the basis for effective and powerful techniques for diverse motif finding applications.

Journal Article↗

PubMed2006

Predicting domain-domain interactions using a parsimony approach.

We propose a novel approach to predict domain-domain interactions from a protein-protein interaction network. In our method we apply a parsimony-driven explanation of the network, where the domain interactions are inferred using linear programming optimization, and false positives in the protein network are handled by a probabilistic construction. This method outperforms previous approaches by a considerable margin. The results indicate that the parsimony principle provides a correct approach for detecting domain-domain contacts.

Databases, Protein↗

PubMed2005

Decentralized formation flying control in a multiple-team hierarchy.

In recent years, formation flying has been recognized as an enabling technology for a variety of mission concepts in both the scientific and defense arenas. Examples of developing missions at NASA include magnetospheric multiscale (MMS), solar imaging radio array (SIRA), and terrestrial planet finder (TPF). For each of these missions, a multiple satellite approach is required in order to accomplish the large-scale geometries imposed by the science objectives. In addition, the paradigm shift of using a multiple satellite cluster rather than a large, monolithic spacecraft has also been motivated by the expected benefits of increased robustness, greater flexibility, and reduced cost. However, the operational costs of monitoring and commanding a fleet of close-orbiting satellites is likely to be unreasonable unless the onboard software is sufficiently autonomous, robust, and scalable to large clusters. This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple team framework. The objective is to divide large clusters into teams of "manageable" size, so that the communication and computation demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using a messaging architecture for networking and threaded applications (MANTA). In this architecture, tasks may be remotely added, removed, or replaced post launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in Matlab, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

Journal Article↗

PubMed1993

Optimal design of a six-bar linkage with one degree of freedom for an anthropomorphic three-jointed finger mechanism.

This research concerns the design of a three-jointed, anthropomorphic, finger mechanism for use as a prosthesis or robotic end-effector. Based on a study of finger configurations for the human hand, a six-bar linkage with one degree of freedom is proposed. A model of the fingertip displacement of the mechanism is derived by a vector analysis approach. The effects of joint friction on the transmission efficiency are analysed. By measuring the joint positions of a human finger, a mathematical model of the pinching and holding configurations are developed. Optimal parameters for the finger mechanism are obtained by non-linear programming based on an objective functional involving motion posture and locus, transmission efficiency and weight subject to geometric and bionic constraints. Simulation results indicate that the mechanism is useful for a variety of prosthetic and robotic applications.

Biomechanical Phenomena↗

PubMed2003

Design of three-dimensional superresolution filters and limits of axial optical superresolution.

Theories to design a three-dimensional superresolution filter (TDSF) for confocal microscopy are proposed that can obtain a globally optimal solution through linear programming. The designed TDSF is proved to be a phase-only element introducing a phase delay of 0 or pi. Five design examples of the TDSF are presented to demonstrate the validity of these theories, Regardless of transverse superresolution, a curve of Seu(Ga+/-) defined as the maximum value of Strehl ratio S under the axial resolving power of Ga+/- is calculated to set the fundamental limits of axial optical superresolution. Finally, what is to our knowledge a novel analytic expression of Seu(Ga+/-) is deduced.

Journal Article↗

PubMed2006

Design and experimental test of diffractive superresolution elements.

By using previously established methods based on linear programming (MLP), we design and fabricate two types of diffractive superresolution element (DSE). The structure parameters and superresolution performances of the fabricated DSEs are tested. The test results agree well with the design results and are applicable to a writable or a read-only optical disk. Thus the application validity of the MLP is experimentally verified.

Journal Article↗

PubMed2002

Theories for the design of diffractive superresolution elements and limits of optical superresolution.

We suggest using the theory of linear programming to design diffractive superresolution elements if the upper bound of the intensity distribution on the input plane is restricted, and using variation theory of functional or wide-sense eigenvalue theory of matrix if the upper bound of the radiation flux through the input plane is restricted. Globally optimal solutions can be obtained by each of these theories. Several rules of the structure and the superresolution performance of diffractive superresolution elements are provided, which verify the validity of these theories and set some limits of optical superresolution.

Journal Article↗

PubMed2003

Theories for the design of a hybrid refractive-diffractive superresolution lens with high numerical aperture.

By geometrical optics and the Rayleigh-Sommerfeld diffraction formula, theories for the design of a hybrid refractive-diffractive superresolution lens (HRDSL) with high numerical aperture are constructed. Differences between the profile of the diffractive superresolution element (DSE) with high numerical aperture and that with low numerical aperture are indicated. Optimization theory can obtain a globally optimal solution through a linear programming much more simplified than the corresponding one in Liu et al. [J. Opt. Soc. Am. A 19, 2185 (2002)]. The rules of the structure of the designed DSE are both theoretically proved and numerically verified. Comparison of this optimization theory with the other design theories and examples of designing the HRDSL with high numerical aperture are provided. Last, some limits of optical superresolution with high numerical aperture are set and compared with those for low numerical aperture.

Journal Article↗

PubMed2005

Design theories and performance limits of diffractive superresolution elements with the highest sidelobe suppressed.

For the application of optical data storage, theories that we present can be used to design a diffractive super-resolution element (DSE) with the highest sidelobe suppressed. A globally optimal solution among general hybrid-type filters can be solved through linear programming. The obtained globally optimal performances set the exact performance limits of a general hybrid-type DSE with the highest sidelobe suppressed. A comparison of our design theories and the previous design methods shows the advantages of the former.

Journal Article↗

PubMed2006

Optical superresolution of focused partially spatially coherent laser beams.

We report design theories of a diffractive superresolution element (DSE) to implement optical superresolution of focused partially spatially coherent laser beams. The design problem of the DSE can be transformed into a problem of linear programming to obtain a globally optimal solution. By using the design theories, some fundamental limits of optical superresolution of focused partially spatially coherent laser beams are proposed, and several design examples are provided. As expected, both the fundamental limits and the design examples show that worse spatial coherence will cause worse superresolution performance. The design theories provide a design approach with partially coherent beams and may be useful for other design problems under partially coherent illumination.

Journal Article↗

PubMed2006

IPRO: an iterative computational protein library redesign and optimization procedure.

A number of computational approaches have been developed to reengineer promising chimeric proteins one at a time through targeted point mutations. In this article, we introduce the computational procedure IPRO (iterative protein redesign and optimization procedure) for the redesign of an entire combinatorial protein library in one step using energy-based scoring functions. IPRO relies on identifying mutations in the parental sequences, which when propagated downstream in the combinatorial library, improve the average quality of the library (e.g., stability, binding affinity, specific activity, etc.). Residue and rotamer design choices are driven by a globally convergent mixed-integer linear programming formulation. Unlike many of the available computational approaches, the procedure allows for backbone movement as well as redocking of the associated ligands after a prespecified number of design iterations. IPRO can also be used, as a limiting case, for the redesign of a single or handful of individual sequences. The application of IPRO is highlighted through the redesign of a 16-member library of Escherichia coli/Bacillus subtilis dihydrofolate reductase hybrids, both individually and through upstream parental sequence redesign, for improving the average binding energy. Computational results demonstrate that it is indeed feasible to improve the overall library quality as exemplified by binding energy scores through targeted mutations in the parental sequences.

Algorithms↗