The fleet assignment problem (FAP) assigns the type of airplane at each flight segment. Since airplane is an expensive resource, poor fleet assignment can cause a great increase in costs of airlines. There are so many consideration which should be tackled in formulation of a FAP problem, especially the parameters regarding to the airplanes. This paper presents a novel, mixed integer programing ...

The urban planning is required to direct the cities development based on the sustainable use of its territory. On the other hand, Answer Set Programming (ASP) is a logic programming paradigm with the ability of non-monotonic reasoning, which has contributed to solving complex problems in a short period of time, providing a considerable number of possible outcomes to the same problem. The treatm...

Fleet planning is a process of strategic importance for an airline. Airlines have a tendency to match their capacities and passenger demand for corresponding market conditions, which has a direct impact on airline profitability and costs. It is necessary to consider many different factors in order to make a good fleet plan. This paper proposes the sequential two-stage model for fleet planning. ...

imagine you have traveled to an unfamiliar city. before you start your daily tour around the city, you need to know a good route. in network theory (nt), this is the traveling salesman problem (tsp). a dynamic programming algorithm is often used for solving this problem. however, when the road network of the city is very complicated and dense, which is usually the case, it will take too long fo...

The rapid proliferation of community-based health education programs has out-paced the knowledge base of behavior change strategies that are appropriate and effective for public health interventions. However, experiences from a variety of large-scale studies suggest that principles and techniques of social marketing may help bridge this gap. This article discusses eight essential aspects of the...

While most current work in POMDP planning focus on the development of scalable approximate algorithms, existing techniques often neglect performance guarantees and sacrifice solution quality to improve efficiency. In contrast, our approach to optimizing POMDP controllers by probabilistic inference and obtaining bounded on solution quality can be summarized as follows: (1) re-formulate POMDP pla...

This study proposes an integrated, reverse logistics supply chain planning process with modular product design that produces and markets products at different quality levels. A mixed integer programming (MIP) model formulates the overall planning process required to maximize profit by considering the collection of returned products, the recovery of modules and the proportion of the product mix ...

The unlikely mix of the above topics conspire powerfully to provide a solid basis for autonomous robot navigation support in known, initially unknown and time varying environments. This presentation explores some of the relationships involving Computational Geometry, Image Processing and Path Planning in the context of Intelligent Robotics, with a variety of experimental case studies to demonst...

Case-based reasoning is a problem solving method that uses stored solutions to problems to aid in solving similar new problems. One of the difficulties of case-based reasoning is identifying cases that are relevant to a problem. If the problem is defined on a geometric domain — for instance, planning a route using a city map — it becomes possible to take advantage of the geometry to simplify th...