Titlebook: Marketingforschung und K?uferverhalten; Heribert Meffert Book 1992Latest edition Betriebswirtschaftlicher Verlag Dr. Th. Gabler, Wiesbaden

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the cost of moving heavy items (as is the case in the steel industry). We propose two heuristics, one Evolutionary Algorithm (EA) adapted from a similar problem in the literature, and a novel Biased Random Key Genetic Algorithm (BRKGA). Computational results show that BRKGA outperforms the evolution

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Heribert Meffertbook is a perfect guide for graduate students, researchers and professionals willing to applying metaheuristic algorithms in civil engineering and other related engineering fields, such as mechanical, transport and geotechnical engineering. It is also a valuable aid for both lectures and advanced en

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Heribert Meffertg processes and create additional more massive datasets for the long-term tracking of various phenomena. This chapter focuses on the MIR from infrared and optical sensors relying on the Particle Swarm Optimization (PSO) class of algorithms. These computational intelligence procedures circumvent prob

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Heribert Mefferttier of multi-objective bilevel problems. The second methodology is a decision maker oriented approach, where preferences from the upper level decision maker are incorporated in the intermediate steps of the algorithm, leading to reduced computational expense. Both these methodologies are tested on

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determine what is an acceptable solution and what is reasonable amount of time. For instance, some timetabling problems (e.g., scheduling of courses at University) are notoriously difficult because they include many constraints. Therefore, an acceptable solution in this context could be one that vi

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Heribert Meffert even a partition of vertices. In this chapter we present a general overview of the more relevant works regarding the application of ant colony based algorithms for dynamic optimization problems. We will also highlight the mechanisms used in different implementations found in the literature, and thu

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Heribert Meffertthe subpopulation members converging to that basin. The proposed niching strategy is incorporated into the state-of-the-art evolution strategies, and the resulting method is compared with some of the most successful multimodal optimization methods on composite test problems. A comparison of numerica