Several studies in the last two decades have investigated the role of built environment on walking. Studies that investigated the role of built environment on walking to transit analyzed the role of various destinations in proximity to the stations. However, few studies have investigated the role of these destinations on walking trip generation at the origin of the trip. Moreover, none of these studies have investigated the role of availability of public services on walking to transit. This study identifies the urban services at the origin of walking trips of the tri-rail commuters in the West Palm, Broward, and Miami-Dade Counties of South Florida. The number of pedestrian users of tri-rail stations and the available urban service were aggregated per Traffic Analysis Zones and analyzed using standard Poisson regression. Findings indicate that availability of urban services such as public education and public recreation have a positive effect on walking to commuter-rail. Implications of this study include the identification and development of Capital Improvement Projects such as libraries to be located in close proximity to schools and colleges. New and proposed train stations should be located in proximity to urban services such as school, colleges, and libraries to encourage pedestrian users.

 In real time situations, the total availability of goods or product may be more or less than the actual market demand and the unbalanced transportation situation arise more commonly. Such unbalanced Transportation Problems (TP) are solved by introducing dummy source or destination which do not exist in reality. The optimal allocation involves cells from such dummy source or destination and the allocated number of quantities are held back at one or more origins. The paper aims to propose an algorithm based on Absolute Points to solve unbalanced TP under fuzzy environment. The proposed algorithm is advantageous than the existing algorithms  in such a way that it provides the added information of transporting the excess availability from dummy supply point to appropriate destination to meet future demands at minimum cost. Finally, by virtue of the proposed algorithm an example is done to illustrate the practicality and the effectiveness of the proposed algorithm. 

In this paper k-obnoxious facility location problem has been modeled as a pure planner location problem.  Area restriction concept has been incorporated by inducting a convex polygon in the constraints set. A linear programming iterative algorithm for k- obnoxious facility locations has been developed. An upper bound has been incorporated in the algorithm to get the  optimal solution. Also the concept of upper bound has reduced  the number of linear programming problems to solved in the algorithm. Rectilinear distance norm has been considered as the distance measure as it is more appropriate to the various realistic situations. 

The aim of the research article is not only to propose a solution procedure to solve multi-objective fuzzy stochastic programming problem by using genetic-algorithm-based fuzzy programming method, but also to apply the computational techniques for transportation of the hazardous waste materials. In this article, routing and siting problems for nuclear hazardous waste material are studied and solved. The amount of waste materials generated in the nuclear reactors follows normal distribution. The two considered objective functions are about route selection which includes minimum travel time and minimum number of houses along the way, taking the safety measures into consideration. A multi-objective fuzzy stochastic mathematical model is formulated with the above mentioned objective functions and the route selection as the constraints. The proposed solution procedure is illustrated by a numerical example and a case study.