High freight and passenger-carrying capacity, providing a fast and safe journey, and its tourism potential, railway transportation remains preferable among transportation types. Many personnel perform different tasks ...
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High freight and passenger-carrying capacity, providing a fast and safe journey, and its tourism potential, railway transportation remains preferable among transportation types. Many personnel perform different tasks such as operation, administration, maintenance, security, and cleaning on the railways to provide an excellent service to the passengers. These personnel are among the most critical parts of the railway system in infrastructure, passenger, and freight transport. This study aims to create a schedule by using mathematical methods for the personnel working in the railway system. The goal programming method, which enables to achieve more than one goal simultaneously, was used to solve the problem. It is planned to create the most appropriate and efficient work plan by analyzing the work, task distribution, and shift schedules of the personnel working on the high-speed railway (HSR) Ankara-Istanbul line. The 28 day team schedule, which aims to distribute the duties of the staff equally, includes the distribution of the teams and the creation of tours for a total of sixteen daily trips. 225 crew working between Ankara-Istanbul and Istanbul-Ankara were formed. We gathered a fair schedule for the crew, and we increased the satisfaction level of the personnel. While all this is being done, the business requests were met.
The literature on multiple objective programming contains numerous examples in which goal programming is used to plan a selection of inputs to secure desired outputs that will conform 'as closely as possible' ...
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The literature on multiple objective programming contains numerous examples in which goal programming is used to plan a selection of inputs to secure desired outputs that will conform 'as closely as possible' to a collection of (possibly conflicting) objectives. In this paper the orientation is changed from selection to evaluation and the dual variables associated with goal programming are brought into play for this purpose. The body of the paper is devoted to an example in portfolio planning modelled along lines like those used by Konno and Yamazaki where closeness to risk and return objective is measured in sums of absolute deviations. An appendix then shows how such a use of dual variables may be applied to evaluate least absolute value (LAV) regressions relative to their sensitivity to data variations. Simple numerical examples are used to illustrate the potential uses of these dual variable values for evaluation in more complex situations that include determining whether an efficiency frontier has been attained. (C) 1997 Elsevier Science B.V.
There have been significant advances in the theory of goal programming (GP) in recent years, particularly in the area of intelligent modelling and solution analysis. The intention of this paper is to provide an overvi...
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There have been significant advances in the theory of goal programming (GP) in recent years, particularly in the area of intelligent modelling and solution analysis. The intention of this paper is to provide an overview of these developments, to detail and assess the current state-of-the-art in the subject, and to highlight areas which seem promising for future research. Modelling techniques such as detection and restoration of pareto efficiency, normalisation, redundancy checking, and non-standard utility function modelling are overviewed. The connection between GP and other multiobjective-programming techniques as well as a utility interpretation of GP are examined. The rationality of ranking Multi-Criteria Decision Making techniques, and of placing GP in such a ranking, is discussed. (C) 1998 Elsevier Science B.V. All rights reserved.
One of the benefits of implementing transportation infrastructure projects is the maximization of network accessibility performance, so that system users' mobility is optimized. However, infrastructure investment ...
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One of the benefits of implementing transportation infrastructure projects is the maximization of network accessibility performance, so that system users' mobility is optimized. However, infrastructure investment decisions rarely consider stakeholders' preferences to network performance measures and the impact of project selection and prioritization on the network accessibility performance. This paper presents a goal programming framework that considers network accessibility performance and the total cost of road infrastructure projects or project bundles to prioritize investments, taking into account stakeholders' preferences to the performance criteria. Results of the case study using the low-volume road (LVR) network showed that the accessibility benefits of LVR projects depend on their relative spatial location in the network, their total project cost, target performance goals, and stakeholders' preferences to performance criteria. The study results also showed that LVR projects could maximize network accessibility even after the occurrence of network disruption events. Therefore, the proposed framework could help the decision-makers develop efficient infrastructure investment plans to mitigate natural and human-made network disruption events.
作者：
Ryan, MJUniv Hull
Dept Econ Kingston Upon Hull HU6 7RX N Humberside England
In this paper a new class of goal programming models are employed to define economies of scale and scope first with reference to distribution models and then with reference to more general linear and nonlinear goal pr...
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In this paper a new class of goal programming models are employed to define economies of scale and scope first with reference to distribution models and then with reference to more general linear and nonlinear goal programming models. Applications to interregional production, regulation and exchange are provided and in every case these models yield "competitive" results as special cases. But in their general form the models and associated results correspond to appropriately regulated market conditions with regulation being determined inter alia by means of appropriate supply and/or demand goal oriented taxes and subsidies. (C) 2002 Elsevier B.V. All rights reserved.
The priority method on the intuitionistic fuzzy preference relation (IFPR) is proposed. In order to avoid the operational difficulty in dealing with the intuitionistic sets, the equivalent interval matrices of the IFP...
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The priority method on the intuitionistic fuzzy preference relation (IFPR) is proposed. In order to avoid the operational difficulty in dealing with the intuitionistic sets, the equivalent interval matrices of the IFPR are introduced. Based on the multiplicative consistent definition of the fuzzy interval preference relation (FIPR), the goal programming models for deriving the priority vector of the IFPR have been put forward by analyzing the relation between the IFNPR and the IFPR. This goal programming method is generalized to the case of group decision making with the weight information defined by each DM. Two numerical examples are provided to illustrate the application of the proposed models. (C) 2009 Elsevier Ltd. All rights reserved.
The study of cognitive biases in decision-making has largely arisen within the context of the subjective expected utility school of decision analysis. Many of the behavioural patterns that have been discovered do seem...
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The study of cognitive biases in decision-making has largely arisen within the context of the subjective expected utility school of decision analysis. Many of the behavioural patterns that have been discovered do seem to be relevant to broader areas of multicriteria decision analysis (MCDA). In this paper, we look specifically at the judgemental inputs required in implementing goal programming ( GP) models. The potential relevance of some of the known cognitive biases in this context are identified, and their impact studied by means of simulation experiments. It is found, inter alia, that biases due to anchoring and adjustment and to avoidance of sure loss can lead to substantial degradation in the performance of GP algorithms. Suggestions for practice and recommendations for follow-up research are derived from the simulation results.
This paper proposes and examines the use of several stock-related factors, called extended factors, for portfolio selection. These factors, including the traditional factors of risk and return, are represented as obje...
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This paper proposes and examines the use of several stock-related factors, called extended factors, for portfolio selection. These factors, including the traditional factors of risk and return, are represented as objectives in weighted goal programming (WGP) models. Several WGP models with passive and active target values and various weights for their unwanted deviational variables in their achievement functions have been developed. The weights and target values of the extended factors represent decision makers' utility toward their portfolio. The resulting portfolios for the proposed models are compared against each other as well as against the Dow Jones Industrial Average index and portfolios obtained from the well-established Markowitz and Konno and Yamazaki's models. The experimental results strongly support the use of extended factors for portfolio selection problems and the assumption of meeting decision maker's preferences and utilities better than the portfolios based entirely on risk and return.
goal programming (GP) is applied to modelling the decision making processes in the well-known Ultimatum Game and some of its variations. The decision model for a player is a Chebychev GP model that balances her indivi...
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goal programming (GP) is applied to modelling the decision making processes in the well-known Ultimatum Game and some of its variations. The decision model for a player is a Chebychev GP model that balances her individual desires with the mental model she has of the desires of other relevant players. Fairness is modelled as a universal mechanism, allowing players to differ in their belief of what a fair solution should be in any particular game. The model's conceptual framework draws upon elements considered of importance in the field of cognitive neuroscience, and results from the field of psychology are used to further specify the types of goals in the model. Computer simulations of the GP models, testing a number of Ultimatum, Dictator and Double-Blind Dictator Games, lead to distributions of proposals made and accepted that correspond reasonably well with experimental findings.
This study proposes a new use of goal programming (GP) for time-series regression, along with a related computer algorithm. The most important feature of this newly proposed GP use is that it can incorporate Serial Co...
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This study proposes a new use of goal programming (GP) for time-series regression, along with a related computer algorithm. The most important feature of this newly proposed GP use is that it can incorporate Serial Correlation (SC) in its time-series analysis. As an important case study, this research applies the proposed GP/SC technique to a real data set related to Japanese telecommunications (1953-1991). Four policy suggestions are documented for use in the future development of Japanese information infrastructure. (C) 1998 Elsevier Science Ltd. All rights reserved.
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