(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No.7, 2017 337 | Page www.ijacsa.thesai.org A Novel Modeling based Agent Cellular Automata for Advanced Residential Mobility Applications Elarbi Elalaouy*, Khadija Rhoulami & Moulay Driss Rahmani LRIT associated unit to CNRST (URAC°29), Faculty of Science, Mohammed V University in Rabat 4 Av.Ibn Battouta B.P. 1014 RP, 10006 Rabat, Morocco Abstract—Nowadays, residential mobility (RM) is usually interconnected with other urban phenomena to give more realistic and effective to the simulation models in order to support urban planners and decision makers. Recent RM research works to describe models from a functional view; however researchers do less focus in providing software modeling of their RM applications. Based on this note, the article presents an agent cellular automata based modeling for advanced RM applications. The proposed modeling contains six models based on UML 2.0 diagrams which models parts of the system from different views. The work could be of interest for specialists (researchers, designers and developers) when modeling advanced RM applications. Keywords—Residential mobility, multi agent systems, cellular automata; urban modeling I. INTRODUCTION Residential mobility (RM) is a very complex phenomenon that had first been studied as an independent system. This tendency is the classical point of view. However, the present tendency is focusing on to interconnect residential mobility with other urban phenomena with which it could give more realistic and effectiveness to the based simulation computer models in order to supporting urban planning and decision making. For example, authors of [1]-[4] had developed simulation’s models integrating residential mobility, housing choice, population growth and land use change in order to simulate residential mobility for different duration of years. Such research works of residential mobility do describe models from a functional view. They describe equations, functions, algorithms that run and simulate models. However, what could be noticed is that scholars do less focus on providing software modeling of their residential mobility’ applications. Departing from this notice, this article propose a novel agent cellular automata based modeling for advanced residential mobility applications. This work gets benefit from development and coding experiments and apprehension of existent simulation models [1], [2], [5], [6]. Residential mobility, housing choice, population growth and land use dynamics are urban processes to be modeled; modeling such urban processes is not a simple task. Author of [7] had reported that a great part of challenge is the modeling of interconnections of urban processes that are resulting in a complex spatial and dynamic behavior. To contribute in overcoming this challenge, a novel modeling is proposed which answers to how to model land use, population of an urban area and their dynamics and how to interconnect the four mentioned urban processes in order to keep track of the outputs of the simulation over a calendar of time. The paper is structured as follows: the work is put firstly into its context by presenting some related conventional and advanced RM models; secondly, it outlines specifications of advanced RM models, justifies the use of agent cellular automata approach and then presents the proposed novel modeling with its sub-models. Finally, a conclusion is given to highlight usefulness of this model for boosting modeling, coding and development of residential mobility applications. II. CLASSICAL AND ADVANCED RM MODELS Residential mobility is a topic of large concern to urban researchers [8]-[14]. It concentrates on causes, effects and statistic rates of households’ relocation decision of an urban area. A good understanding of causes, effects and rates would be of great help for urban planners and decisions makers. Residential mobility models could be classified on two categories conventional and advanced models. Conventional models [9], [15]-[17] are concentrating on rates of mobility for different households categories. It uses generally cross sectional census data and tries to answer to questions such as why an urban area is representing a big rate of mobility, why a member or household category move frequently. These studies are limited in goals, and focus only on understanding drivers and effects of residential mobility for a given urban area. With advancement in computer algorithms and GIS spatial analysis, advanced residential mobility models are gradually replacing conventional models. These models combine in addition to residential mobility other urban processes such as housing choice, urban growth, transport system, etc. [18], [19] [3], [4]. Models of this category use series of socioeconomic census data, households’ census data, demographic data and spatial data. Models of these complex systems could be constructed only if urban systems are considered as spatial, dynamic, self-organizing and computational systems. III. SPECIFICATION OF ADVANCED RM MODELS Residential mobility is a phenomenon that takes place in an urban city over a calendar of years. Households could decide yearly to move from one location to another. When they decide to move, then subsequently they decide to choose a new housing. Decision of relocation is an algorithm that uses households’ learning census data and decides if a given household desire to move to a new housing or not. After decision of relocation comes Housing Choice which is also an