Best Combination Of Options Research Articles

Troels Staehelin Jensen-dissecting pain.

Troels Staehelin Jensen-dissecting pain.

Returnable packaging as a sustainability factor in the automotive chain: a case study.

Packaging makes a valuable contribution to economic, environmental and social sustainability through product protection, waste prevention, enabling efficient business conduct and providing consumers with the benefits of the products it contains. The case study chosen for the work was carried out in a multinational automotive company with the objective of researching the financial and environmental factors in the substitution of one-way packages by the returnable ones during the distribution of parts for automotive dealers. There is no single solution to manage packaging waste. The best combination of options depends on local conditions, especially demographics and the degree of investment made in modern processing systems. Determining the best combination of options for managing packaging waste therefore requires detailed case-by-case analysis where life-cycle assessments can provide valuable decision support.

外部環境要因の不確実性を定量化した事業価値評価の支援手法

This research addresses an evaluation method of business value considering risk-hedging options from the first stage of the product development. A scenario planning method is introduced into the estimating method of the business value in order to identify uncertain factors, which affect to the business value. Generally, the scenario planning method has a weak point that it is difficult to apply its result into the project plan, because the specified factors are relatively qualitative. Proposed uncertainty analysis organizes the qualitative factors into four types of stochastic distributions. By combining the risk-hedge options and probabilistic distributions, a decision tree diagram, which contains the numerical estimated values about product development project, is calculated. The decision tree diagram describes project's EPV (Expected Present Value), so that the best combination of options is derived. The proposed method is applied to the i-Painter development project, which is automatic repairing robot of the buildings as an example. Two risks about future technological change in painting mechanics and flooding around factory are identified, calculated, and compared. The application result shows that the proposed method can surely help the development member to specify the economical external element change. In addition, the result indicates that the best business value is estimated and best risk hedge option can be calculated.

Bound constrained interval global optimization in the COCONUT Environment

We introduce a new interval global optimization method for solving bound constrained problems. The method originates from a small standalone software and is implemented in the COCONUT Environment, a framework designed for the development of complex algorithms, containing numerous state-of-the-art methods in a common software platform. The original algorithm is enhanced by various new methods implemented in COCONUT, regarding both interval function evaluations (such as first and second order derivatives with backward automatic differentiation, slopes, slopes of derivatives, bicentered forms, evaluations on the Karush---John conditions, etc.) and algorithmic elements (inclusion/exclusion boxes, local search, constraint propagation). This resulted in a substantial performance increase as compared to the original code. During the selection of the best combination of options, we performed comparison tests that gave empirical answers to long-lasting algorithmic questions (such as whether to use interval gradients or use slopes instead), that have never been studied numerically in such detail before. The new algorithm, called coco_gop_ex, was tested against the prestigious BARON software on an extensive set of bound constrained problems. We found that in addition to accepting a wider class of bound constrained problems and providing more output information (by locating all global minimizers), coco_gop_ex is competitive with BARON in terms of the solution success rates (with the exception of a set of nonlinear least squares problems), and it often outperforms BARON in running time. In particular, coco_gop_ex was around 21 % faster on average over the set of problems solved by both software systems.

Distillation column targets

This paper relates to the design of distillation columns. In particular, it relates to the optimisation of a base case design. Column optimisation involves options such as different reflux ratios, pressures, side condensing/reboiling and feed preheating/cooling. We need to establish heat loads and temperature levels for such modifications and identify the best combined options. The paper presents a methodology based on a combination of thermodynamics and practical aspects of column modification. The methodology gives the engineer targets for design options ahead of design. In addition, it provides targets for the best combination of options. Alongside heat load and temperature targets, the methodology clarifies the effect of design modifications on column capital cost, also ahead of design. The methodology is applicable to nonideal multicomponent systems and complex distillation configurations. There are downstream applications involving distillation column integration in the overall processes and column sequencing. The methodology has been tested in industrial applications involving ethylene, LNG and refinery columns.

An expert system for choosing the best combination of options in a general purpose program for Automated Design Synthesis

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Cost-Minimization Model for Reducing Sulphur Dioxide Emission from Coal-Fired Generating Stations

Abstract To limit emission of sulphur dioxide, an electrical utility has several available options: (i) Burn low-sulphur coal, (ii) remove SO2 from flue gases after combustion (Flue Gas Desulphurization or FGD), and (iii) remove sulphur from coal before combustion (Physical Coal Cleaning or PCC). Options (ii) and (iii) vary in their cleaning capabilities and scale economies. Pre-cleaning of coal followed by post-cleaning of flue gases may thus be less costly than either PCC or FGD alone to obtain a given level of sulphur removal. A mathematical programming model to determine the best combination of options is developed from empirical cost data and solved for typical conditions encountered by North American utilities. Sensitivity analyses are carried out with respect to the various operating and capital costs, as well as the maximum SO. emission level. The latter enables assessment by the regulatory authorities of proposed environmental standards. Finally, we show how the model can aid a utility in directi...