Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm versus Column Generation Method

Airline crew cost is the second-largest operating cost component and its marginal improvement may translate to millions of dollars annually. Further, it's highly constrained-combinatorial nature brings-in high impact research and commercial value. The airline crew pairing optimization problem (CPOP) is aimed at generating a set of crew pairings, covering all flights from its timetable, with minimum cost, while satisfying multiple legality constraints laid by federations, etc. Depending upon CPOP's scale, several Genetic Algorithm and Column Generation based approaches have been proposed in the literature. However, these approaches have been validated either on small-scale flight datasets (a handful of pairings) or for smaller airlines (operating-in low-demand regions) such as Turkish Airlines, etc. Their search-efficiency gets impaired drastically when scaled to the networks of bigger airlines. The contributions of this paper relate to the proposition of a customized genetic algorithm, with improved initialization and genetic operators, developed by exploiting the domain-knowledge; and its comparison with a column generation based large-scale optimizer (developed by authors). To demonstrate the utility of the above-cited contributions, a real-world test-case (839 flights), provided by GE Aviation, is used which has been extracted from the networks of larger airlines (operating up to 33000 monthly flights in the US).Comment: 7 pages, 3 figure

Designing a Frequency Selective Scheduler for WiMAX using Genetic Algorithms

Projecte final de carrera fet en col.laboració amb University of Stuttgar

Shaper-GA: automatic shape generation for modular housing

This work presents an automatic system that, from the specification of an architectural language of design, generates several alternative floor plants for the construction of modular homes. The system uses Genetic Algorithms and is capable of efficiently producing various plant solutions. The rules of architecture are implemented in the fitness function translating the rules of a Shape Grammar created by the architect. Different solutions of feasible plants are generated, that is, solutions that obey the rules of Shape Grammar and do not have overlays between the rooms. The system can be integrated with a user-friendly interface in the future, to allow for the house owners customization of their own house. Such a tool can also be delivered to construction companies for them to manage the design of modular houses that meet specific clients requirements.Este trabalho apresenta um sistema automático que, a partir da especificação de uma linguagem arquitetural de design, gera plantas alternativas para residências de construção modular. O sistema usa Algoritmos Genéticos e é capaz de produzir várias soluções de plantas de modo eficiente. As regras de arquitetura são implementadas na função de fitness a partir de uma Gramática de Forma criada pelo arquiteto. São geradas diferentes soluções de plantas exequíveis, isto é, soluções que obedecem à Gramática de Forma e não têm sobreposições entre as suas divisões. Pode ser futuramente integrado com uma interface amigável para o utilizador de forma a que este personalize e crie a sua futura casa. Tal ferramenta pode também ser entregue às companhias de construção de forma a que estas gerem uma planta para uma casa modular personalizada

Optimizing production scheduling of steel plate hot rolling for economic load dispatch under time-of-use electricity pricing

Time-of-Use (TOU) electricity pricing provides an opportunity for industrial users to cut electricity costs. Although many methods for Economic Load Dispatch (ELD) under TOU pricing in continuous industrial processing have been proposed, there are still difficulties in batch-type processing since power load units are not directly adjustable and nonlinearly depend on production planning and scheduling. In this paper, for hot rolling, a typical batch-type and energy intensive process in steel industry, a production scheduling optimization model for ELD is proposed under TOU pricing, in which the objective is to minimize electricity costs while considering penalties caused by jumps between adjacent slabs. A NSGA-II based multi-objective production scheduling algorithm is developed to obtain Pareto-optimal solutions, and then TOPSIS based multi-criteria decision-making is performed to recommend an optimal solution to facilitate filed operation. Experimental results and analyses show that the proposed method cuts electricity costs in production, especially in case of allowance for penalty score increase in a certain range. Further analyses show that the proposed method has effect on peak load regulation of power grid.Comment: 13 pages, 6 figures, 4 table