Spanning Tree Approach On The Snow Cleaning Problem

Snow cleaning is one of the important tasks in the winter time in Sweden. Every year government spends huge amount money for snow cleaning purpose. In this thesis we generate a shortest road network of the city and put the depots in different place of the city for snow cleaning. We generate shortest road network using minimum spanning tree algorithm and find the depots position using greedy heuristic. When snow is falling, vehicles start work from the depots and clean the snow all the road network of the city. We generate two types of model. Models are economic model and efficient model. Economic model provide good economical solution of the problem and it use less number of vehicles. Efficient model generate good efficient solution and it take less amount of time to clean the entire road network.

A proposed Model for Country Branding : an experimental Application on Nigeria

In the era of globalization, countries compete with each other for attention, respect and trust of potential consumers, investors, tourists, media and governments of other nations. Branding is the most powerful tool that a nation can utilize for effective differentiation strategies and for creating competitive advantage over other nations. Unfortunately, not every nations or destination marketers have a broad understanding of the concept of branding and how a country can be successfully branded. Hence, this study has proposed a model that could be used as a valuable guide for country branding. Also the model is recommended for countries struggling with image crisis; on the mission to improve the image internationally. Nigeria is a good example of countries with image crisis; it is one of the most populated countries in the world with a population of about 160 million inhabitants and growth rate of 2.553percent annually. Despite the abundant resources (e.g. coal, petroleum, natural gas etc.) that the nation is endowed with, it is quite disappointing that the population below poverty line is still at the alarming rate of 70percent of the total population. The mismanagement and poor leadership of the nation characterised by corruption, fraud, embezzlement of public fund etc. has culminated into serious image crisis that is slowing down the potential for investment and economic growth. However, there has been series of image rebranding campaigns but no tangible achievement has been recorded. It is quite questionable though, if image rebranding will provide the kind of future that Nigeria envisaged, considering the socio-political situation and the economic imbalance; compounded by the obvious fact that the nation has no known brand. Therefore, this paper argues that there is need to redirect the effort invested on image rebranding to the creation of a unique and competitive brand for the country. It was established from the study that a nation’s brand is capable of improving the reputation of the nation as well as stimulate the expectation of the target audience. However, it was also established from the study that a wrong approach to branding could mislead the target audience and attract negative publicity. Hence, as a contribution of the study to the field of branding, a model was proposed as a functional guide for country branding. Also, considering the abysmal performance of Nigeria’s image in the international community and to strengthen the argument that brand creation is required for the country; an experimental application of the proposed model was conducted using Nigeria as the case country. The first phase of the model suggested a major improvement in the society; this is required to further enhance the strengths of the country and to motivate the much needed community participation and confidence in the brand creation. It is the conclusion of the study that a strong nation brand can offset the image problem if it is built on something concrete, genuine, and uniquely identifiable with the country, capable of connecting to the cognitive psychology of the target audience.

Heuristic optimization of the p-median problem and population re-distribution

This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution.   The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis.   Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling. 

An empirical test of the gravity p-median model

A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Distance measure and the p-median problem in rural areas

The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

Testing the gravity p-median model empirically

Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.