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 Gest？o & Produ？？o , 2012, DOI: 10.1590/S0104-530X2012000100009 Abstract: this study aims to evaluate the quality of the solutions for facility location-allocation problems generated by a gis-t (geographic information system for transportation) software. these solutions were obtained from combining the facility location and transportation problem routines, when compared with the optimal solutions, which were obtained using the exact mathematical model based on the mixed integer linear programming (milp) developed externally to the gis. the models were applied to three simulations: the first one proposes set up businesses and customers' allocation in the state of s？o paulo; the second involves a wholesaler and an investigation of distribution center location and retailers' allocation; and the third one locates day-care centers in an urban context allocating the demand. the results showed that when the facility capacity is considered, in addition to determine different locations for the new facilities, the optimal milp model can produce results that are 37% better than those of gis.
 Megaron , 2009, Abstract: The main component of accessibility in urban areas is the relation between the transportation network and land use. Improvements in technology have an effective role on the location of urban functions on behalf of urban transportation networks in addition to the economic and social life in the cities. In some cases, technological improvements in the transit systems demonstrate positive and beneficial solutions for the citizens. However, the increasing use of individual automobiles in the cities constitutes one of the most consequential difficulties. The number of automobile owners is stated to be an indicator of the advanced level of cities; however, when the rail or sea transit systems are insufficiently developed and/or when integration between the transit systems is lacking, the use of individual automobiles in daily urban travels escalates dramatically. Such a situation results in serious accessibility problems especially in the historical core of the cities, which are often not planned or developed for vehicular traffic. Under these circumstances, besides the intensive use of social and cultural activities, the speculative aims hasten the deterioration process of the historical districts and cause secondary effects in the form of noise, visual and aesthetic pollution. The Historic Peninsula in Istanbul Metropolitan Area is experiencing the above-mentioned challenges. This article puts forward the importance of the transportation network and its effects on the location of urban facility areas such as administration, education and health, which comprise the whole metropolitan area or national scale of facilities throughout the history in the Historic Peninsula. Finally, based on the hypothesis, the statistical evaluation methods of data collection and interval surveys, which were applied at sample urban facilities during the case study, were analyzed. Furthermore, the criteria for the interaction of transportation and location of urban facilities highlighted by the study are discussed. One of the striking implications is the existence of urban facility areas situated in the Historic Peninsula, which attract both metropolitan and national scale trips during the day. Today, in transportation and urban land use planning, the facilities are drawing high volumes of vehicular and pedestrian traffic out of the historic parts; however, in contrast, the Historic Peninsula is complicated and fully motorized. Furthermore, the limited building lot sizes, which cannot respond to the growing population, raises the issue of decentralization of urban facilities that
 Advances in Management and Applied Economics , 2011, Abstract: The combinatorial nature of integer programming is inevitable even after taking specific model structure into consideration. This is the root problem in implementing large-scale nonlinear integer programming models regardless of which algorithm one chooses to use. Consequently, we suggest that the size of origin-destination be moderate. In the case of large origin-destination problems, more information on the size of Xij is needed to drastically reduce the dimensionality problem. For instance, if Xij is to be greater than the threshold value to be eligible for the rate break, computation time can be noticeably reduced. In the case of large right-hand-side constraints, we suggest scaling these values to the nearest thousands or millions. The approach from Excel proposed in this paper is particularly appropriate if one can balance the sizes of origindestination and right-hand-side constraints in such a way that computation time is not excessive. For a large-scale problem, one must exploit the structure of the model and acquire more information on the bounds of discrete variables. Our approach certainly provides an alternative way to solve nonlinear integer programming models with virtually all kinds of algebraic functions even for laymen who do not feel comfortable with mathematic programming jargons.
 David Benson-Putnins Mathematics , 2014, Abstract: We expand on a result of Barvinok and Hartigan to derive asymptotic formulas for the number of integer and binary integer points in a wide class of multi-index $k_1\times k_2\times \ldots \times k_{\nu}$ transportation polytopes. A simple closed form approximation is given as the $k_j$s go to infinity.
 Journal of Applied Sciences , 2012, Abstract: Managers regularly make decisions pertaining to the effective and efficient allocation of resources to various activities in meeting organizational objective. The task of deciding the optimum plan for distributing goods at the lowest cost possible is a case in point. Minimizing cost of transportation is fundamental for companies in the midst of highly competitive business environment. This study highlights the application of linear programming and spreadsheet that facilitate managers in a Malaysian Trading Company in determining the optimum transportation plan that leads to the lowest transportation cost of polymer from four plants to four demand destinations. It also discusses sensitivity technique in analyzing the impact of uncertainty of unit shipping cost to the total shipping cost of the trading company.
 Mehmet BASTI AJIT-e : Online Academic Journal of Information Technology , 2012, DOI: 10.5824/1309-1581.2012.2.004.x Abstract: In today’s globalized and increasingly competitive environment, organizations’ need to implement successful strategies for supply chain management has become indispensable. Transportation costs within the supply chain comprise an important part of the organizations’ expenses. For this reason, the strategic selection of location is an issue that directly affects supply chain performance and costs. At this stage, it becomes very important to apply the latest and the best methods to the facility location problem. The focus of this study is the p-median problem and its solution techniques, one of the location allocation problems aimed at minimizing the costs arising from shipments between facilities and demand points.
 Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/954249 Abstract: We present a hybridization of two different approaches applied to the well-known Capacitated Facility Location Problem (CFLP). The Artificial Bee algorithm (BA) is used to select a promising subset of locations (warehouses) which are solely included in the Mixed Integer Programming (MIP) model. Next, the algorithm solves the subproblem by considering the entire set of customers. The hybrid implementation allows us to bypass certain inherited weaknesses of each algorithm, which means that we are able to find an optimal solution in an acceptable computational time. In this paper we demonstrate that BA can be significantly improved by use of the MIP algorithm. At the same time, our hybrid implementation allows the MIP algorithm to reach the optimal solution in a considerably shorter time than is needed to solve the model using the entire dataset directly within the model. Our hybrid approach outperforms the results obtained by each technique separately. It is able to find the optimal solution in a shorter time than each technique on its own, and the results are highly competitive with the state-of-the-art in large-scale optimization. Furthermore, according to our results, combining the BA with a mathematical programming approach appears to be an interesting research area in combinatorial optimization. 1. Introduction Heuristics and bioinspired techniques have become efficient and effective alternatives for researchers in solving several complex optimization problems. These types of techniques are able to provide satisfactory solutions for most of the applied problems within acceptable computational times. However, in spite of their effectiveness, these techniques are not able to reach the optimal solution (or ensure its optimality) for large-scale combinatorial optimization problems. In contrast, mathematical programming techniques, particularly the Mixed Integer Programming (MIP), have been studied and developed by scholars over several decades with the main goal of obtaining optimal solutions to difficult problems using as little CPU time as possible. In this case, researchers must face the tradeoff between computational time and the quality of the result. For these reasons, the combination of meta-heuristics and various mathematical approaches has become a well-studied area. Interested readers can find two recent and comprehensive works on the hybridization of stochastic techniques and mathematical programming (MP) approaches in [1, 2]. Swarm Intelligence (SI), as well as other mathematical programming techniques, has been applied successfully to
 BMC Public Health , 2010, DOI: 10.1186/1471-2458-10-142 Abstract: The Epidemiological and Demographic Surveillance System in Kilifi District, Kenya, collects data on vital events and migrations in a population of 220,000 people. We used Geographic Information Systems to estimate pedestrian and vehicular travel times to hospitals and vaccine clinics and developed proportional-hazards models to evaluate the effects of travel time on mortality hazard in children less than 5 years of age, accounting for sex, ethnic group, maternal education, migrant status, rainfall and calendar time.In 2004-6, under-5 and under-1 mortality ratios were 65 and 46 per 1,000 live-births, respectively. Median pedestrian and vehicular travel times to hospital were 193 min (inter-quartile range: 125-267) and 49 min (32-72); analogous values for vaccine clinics were 47 (25-73) and 26 min (13-40). Infant and under-5 mortality varied two-fold across geographic locations, ranging from 34.5 to 61.9 per 1000 child-years and 8.8 to 18.1 per 1000, respectively. However, distance to health facilities was not associated with mortality. Hazard Ratios (HR) were 0.99 (95% CI 0.95-1.04) per hour and 1.01 (95% CI 0.95-1.08) per half-hour of pedestrian and vehicular travel to hospital, respectively, and 1.00 (95% CI 0.99-1.04) and 0.97 (95% CI 0.92-1.05) per quarter-hour of pedestrian and vehicular travel to vaccine clinics in children <5 years of age.Significant spatial variations in mortality were observed across the area, but were not correlated with distance to health facilities. We conclude that given the present density of health facilities in Kenya, geographic access to curative services does not influence population-level mortality.In the 1970s, the incipient Primary Health Care movement brought the international community's attention to the specific health issues facing the poorest members of developing country societies. The "Health for All" doctrine, crystallized at the Alma Ata conference in 1978, advocated for community-based interventions to address health in
 Journal of Transport Literature , 2012, Abstract: The objective of this paper is to use the Geographic Information System (GIS) as a routing tool for urban solid waste (USW) systems. The data from the vehicle used in the USW collection system was put in the GIS database, obtained directly from the company responsible for the service in Itajubá city (MG). With this data, scenarios of the routing system were simulated in GIS, using the GIS ArcRouting algorithm. The goal of the simulations was to evaluate the quality of the current route system and sought solutions that minimize the distance covered by the vehicles and, consequently, the reduction of the involved costs. The general results showed the GIS ArcRouting algorithm to be adequate and as obtaining good results, since that the most important problem’s variables (tax of waste generation and vehicle speed) are attained with precision.
 iBusiness (IB) , 2013, DOI: 10.4236/ib.2013.51B006 Abstract: Many firms have to deal with the problems of scheduling and transportation allocation. The problems of assembly scheduling mainly focus on how to arrange orders in proper sequence on the assembly line with the purpose of minimizing the maximum completion time before they are flown to their destinations. Transportation allocation problems arise in how to assign processed orders to transport modes in order to minimize penalties such as earliness and tardiness. The two problems are usually separately discussed due to their complexity. This paper simultaneously deals with these two problems for firms with multiple identical parallel machines. We formulate this problem as a mixed integer programming model. The problem belongs to the class of NP-complete combinatorial optimization problems. This paper develops a hybrid genetic algorithm to obtain a compromised solution within a reasonable CPU time. We evaluate the performance of the presented heuristic with the well-known GAMS/CPLEX software. The presented approach is shown to perform well compared with well-known commercial software.
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