The Heterogeneous P-median Problem for Categorization Based Clustering
نویسندگان
چکیده
The p-median offers an alternative to centroid-based clustering algorithms for identifying unobserved categories. However, existing p-median formulations typically require data aggregation into a single proximity matrix, resulting in masked respondent heterogeneity. A proposed three-way formulation of the p-median problem explicitly considers heterogeneity by identifying groups of individual respondents that perceive similar category structures. Three proposed heuristics for the heterogeneous p-median (HPM) are developed and then illustrated in a consumer psychology context using a sample of undergraduate students who performed a sorting task of major U.S. retailers, as well as a through Monte Carlo analysis.
منابع مشابه
Fuzzy based efficient drone base stations (DBSs) placement in the 5G cellular network
Currently, cellular networks are one of the essential communication methods for people. Providing proper coverage for the users and also offering high-quality services to them are two of the most important issues of concern in cellular networks. The fifth-generation cellular communication networks can provide higher data transmission rates, which lead to a higher quality of service but this hig...
متن کاملUsing Metaheuristic Algorithms Combined with Clustering Approach to Solve a Sustainable Waste Collection Problem
Sustainability is a monumental issue that should be considered in designing a logistics system. In order to incorporate sustainability concepts in our study, a waste collection problem with economic, environmental, and social objective functions was addressed. The first objective function minimized overall costs of the system, including establishment of depots and treatment facilities. Addressi...
متن کاملAssessment of Clustering Methods for Predicting Permeability in a Heterogeneous Carbonate Reservoir
Permeability, the ability of rocks to flow hydrocarbons, is directly determined from core. Due to high cost associated with coring, many techniques have been suggested to predict permeability from the easy-to-obtain and frequent properties of reservoirs such as log derived porosity. This study was carried out to put clustering methods (dynamic clustering (DC), ascending hierarchical clustering ...
متن کاملA Clustering Based Location-allocation Problem Considering Transportation Costs and Statistical Properties (RESEARCH NOTE)
Cluster analysis is a useful technique in multivariate statistical analysis. Different types of hierarchical cluster analysis and K-means have been used for data analysis in previous studies. However, the K-means algorithm can be improved using some metaheuristics algorithms. In this study, we propose simulated annealing based algorithm for K-means in the clustering analysis which we refer it a...
متن کاملA Novel Hybrid Modified Binary Particle Swarm Optimization Algorithm for the Uncertain p-Median Location Problem
Here, we investigate the classical p-median location problem on a network in which the vertex weights and the distances between vertices are uncertain. We propose a programming model for the uncertain p-median location problem with tail value at risk objective. Then, we show that it is NP-hard. Therefore, a novel hybrid modified binary particle swarm optimization algorithm is presented to obtai...
متن کامل