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The choice to visit a park depends on individual preferences and understanding these preferences will be useful to parks’ management decisions on facilities and infrastructure needs and maintenance. Choice experiment (CE) method is used to inform parks’ management in Kuala Lumpur City, Malaysia on the social values of attributes available at the park. The latent class (LC) model is used to explore the effect of taste heterogeneity on the attributes. The results in the LC models indicate that the most preferred attribute at parks in Kuala Lumpur is recreational facilities. The willingness to pay (WTP) for these facilities range from RM3.25 to RM39.96. This shows that individuals can afford to pay up to RM40.00 per visit for such improvement in the attributes.
Software architectural design has an enormous effect on downstream software artifacts. Decomposition of function for the final system is one of the critical steps in software architectural design. The process of decomposition is typically conducted by designers based on their intuition and past experiences, which may not be robust sometimes. This paper presents a study of applying the clustering technique to support system decomposition based on requirements and their attributes. The approach can support the architectural design process by grouping closely related requirements to form a subsystem or module. In this paper, we demonstrate our experiments in applying the approach to an industrial communication protocol software system and comparing several clustering algorithms. The result obtained from WPGMA (weighted pair-group method using arithmetic averages) shows closer resemblance than other clustering methods to the one developed by the designer.
The purpose of this paper is to develop structural classification of Stochastic Vehicle Routing Problem (SVRP) by different domains and attributes. This research used a systematic review and meta-analysis on SVRP literatures. This includes browsing relevant researches and publications, screening related articles, identifying domains, attributes and categorising the articles based on the identified domains and attributes. The findings of the study show clear differences on the number of studies under each domain and attribute. Most studied attributes are stochastic customer demand, capacitated vehicle, synthesis data and objective function with cost minimization. Whereas the least studied are maximisation objective function, stochastic service time, and an applied model using stochastic with recurs. The research helps to summarise and map a comprehensive survey on SVRP literatures so that various contributions in the field are organised in a manner that provide a clear view for the readers and identify future research directions. This paper is the first of its kind in the field of SVRP that develop a classification scheme for articles published since 1993 to enhances the development of this newly emerging discipline.