Parallelization of population-based evolutionary algorithms for combinatorial optimization problems
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This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and ...
1 Introduction to energy systems and evolutionary algorithms. 2 Genetic Algorithm for Constrained Optimization Models. 3 A Framework for Multi-Objective Evolutionary Algorithms. 4 Thermo-Economic Optimisation of a Solar Thermal Plant. ...
Around three quarters of global resource consumption takes place in urban settlements, with corresponding adverse environmental consequences. According to population forecasts this situation will be exacerbated during the coming years. It is therefore impe ...
Deterministic execution offers many benefits for debugging, fault tolerance, and security. Current methods of executing parallel programs deterministically, however, often incur high costs, allow misbehaved software to defeat repeatability, and transform t ...
In this paper we describe a new computational model of switching between path-planning and cue-guided navigation strategies. It is based on three main assumptions: (i) the strategies are mediated by separate memory systems that learn independently and in p ...
This paper presents a new double hybridized genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The first hybridization adopts embryonic chromosomes as prefixes of variable orders instead of complete variable or ...
In this paper we describe a new methodology for optimising building and urban geometric forms for the utilisation of solar irradiation, whether by passive or active means. For this we use a new evolutionary algorithm(a hybrid CMA-ES/HDE algorithm) to searc ...
We heuristically solve an evacuation problem with limited capacity shelters. An evolutionary learning algorithm is developed for the combined route- and shelter-assignment problem. It is complemented with a heuristic method for the fair minimization of she ...
Current general-purpose memory allocators do not provide sufficient speed or flexibility for modern highperformance applications. To optimize metrics like performance, memory usage and energy consumption, software engineers often write custom allocators fr ...
Current general-purpose memory allocators do not provide sufficient speed or flexibility for modern highperformance applications. To optimize metrics like performance, memory usage and energy consumption, software engineers often write custom allocators fr ...