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Objective reduction in evolutionary multiobjective optimization: Theory and applications
 EVOLUTIONARY COMPUTATION
, 2009
"... Manyobjective problems represent a major challenge in the field of evolutionary multiobjective optimization—in terms of search efficiency, computational cost, decision making, visualization, and so on. This leads to various research questions, in particular whether certain objectives can be omitte ..."
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Manyobjective problems represent a major challenge in the field of evolutionary multiobjective optimization—in terms of search efficiency, computational cost, decision making, visualization, and so on. This leads to various research questions, in particular whether certain objectives can be omitted in order to overcome or at least diminish the difficulties that arise when many, that is, more than three, objective functions are involved. This study addresses this question from different perspectives. First, we investigate how adding or omitting objectives affects the problem characteristics and propose a general notion of conflict between objective sets as a theoretical foundation for objective reduction. Second, we present both exact and heuristic algorithms to systematically reduce the number of objectives, while preserving as much as possible of the dominance structure of the underlying optimization problem. Third, we demonstrate the usefulness of the proposed objective reduction method in the context of both decision making and search for a radar waveform application as well as for wellknown test functions.
Efficient graphbased genetic programming representation with multiple outputs
 International Journal of Automation and Computing
"... Abstract: In this work, we explore and study the implication of having more than one output on a Genetic Programming (GP) graphrepresentation. This approach, called, Multiple Interactive Outputs in a Single Tree (MIOST) is based on two ideas: (a) Firstly, we defined an approach, called Interactivit ..."
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Abstract: In this work, we explore and study the implication of having more than one output on a Genetic Programming (GP) graphrepresentation. This approach, called, Multiple Interactive Outputs in a Single Tree (MIOST) is based on two ideas: (a) Firstly, we defined an approach, called Interactivity Within an Individual (IWI), which is based on a graphGP representation. Secondly, we add to the individuals created with the IWI approach multiple outputs in their structures and as a result of this, we have MIOST. As first step, we analyse the effects of IWI by using only mutations and analyse its implications (i.e., presence of neutrality). Then, we continue testing the effectiveness of IWI by allowing mutations and the standard GP crossover in the evolutionary process. Finally, we tested the effectiveness of MIOST by using mutations and crossover and conduct extensive empirical results on different evolvable problems of different complexity taken from the literature. The results reported in this work, indicate that the proposed approach has a better overall performance in terms of consistency reaching feasible solutions.
A note on designing logical circuits using SAT
 In Proc. 5th Int. Conf. on Evolvable Systems: From Biology to Hardware, ICES’03, volume 2606 of LNCS
, 2003
"... Abstract. We present a systematic procedure for the synthesis and minimisation of digital circuits using propositional satisfiability. We encode the truth table into a canonical sum of at most k different minterms, which is then passed to one randomised search procedure that minimises k. The solutio ..."
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Abstract. We present a systematic procedure for the synthesis and minimisation of digital circuits using propositional satisfiability. We encode the truth table into a canonical sum of at most k different minterms, which is then passed to one randomised search procedure that minimises k. The solution for a minimal k is the satisfiable representation of the resulting circuit. We show how to use an interesting feature of the local search landscape in this minimisation. This approach can be very useful because we can generate exact minimal solutions within reasonably computational resources. 1
Multiple Interactive Outputs in a Single Tree: An Empirical Investigation
 Genetic Programming, 10th European Conference, EuroGP 2007
, 2007
"... Abstract. This paper describes Multiple Interactive Outputs in a Single Tree (MIOST), a new form of Genetic Programming (GP). Our approach is based on two ideas. Firstly, we have taken inspiration from graphGP representations. With this idea we decided to explore the possibility of representing pro ..."
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Abstract. This paper describes Multiple Interactive Outputs in a Single Tree (MIOST), a new form of Genetic Programming (GP). Our approach is based on two ideas. Firstly, we have taken inspiration from graphGP representations. With this idea we decided to explore the possibility of representing programs as graphs with oriented links. Secondly, our individuals could have more than one output. This idea was inspired on the divide and conquer principle, a program is decomposed in subprograms, and so, we are expecting to make the original problem easier by breaking down a problem into two or more subproblems. To verify the effectiveness of our approach, we have used several evolvable hardware problems of different complexity taken from the literature. Our results indicate that our approach has a better overall performance in terms of consistency to reach feasible solutions.
Optimization Methods and Software
, 2005
"... Comparative study of serial and parallel heuristics used to ..."
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Beneficial Aspects of Neutrality in GP
"... In this paper we propose a new approach, called Multiple Outputs in a Single Tree (MOST), to Genetic Programming. The idea of this approach is to specify explicitly Neutrality and study how this improves the evolutionary process. For this sake, we have used several evolvable hardware problems of dif ..."
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In this paper we propose a new approach, called Multiple Outputs in a Single Tree (MOST), to Genetic Programming. The idea of this approach is to specify explicitly Neutrality and study how this improves the evolutionary process. For this sake, we have used several evolvable hardware problems of different complexity taken from the literature. Our results indicate that our approach has a better overall performance in terms of consistency to reach feasible solutions.
Multiobjective Simulated Annealing for Design of Combinational Logic Circuits *
"... Abstract A multiobjective optimization technique was proposed for designing combinational logic circuits with 100% functionality and minimized number of gates. The main idea is to consider each output variant as an objective function, which is assigned to an individual. At first, it evolves each in ..."
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Abstract A multiobjective optimization technique was proposed for designing combinational logic circuits with 100% functionality and minimized number of gates. The main idea is to consider each output variant as an objective function, which is assigned to an individual. At first, it evolves each individual to satisfy the matches between the outputs produced by corresponding output variant of an encoded circuit and the values specified by the truth table. If an individual meets the above matches, it is further evolved to finish matches of the rest of the output variants. Once an individual is feasible, it is optimized in terms of the number of gates. Experiments are carried to assess the performance of multiobjective simulated annealing (MSA) against some intelligent � algorithms and human designs, results illustrate MSA can design combinational logic circuits efficiently.
Evolutionary Computation Group
"... In this paper, we introduce the use of a populationbased selection scheme in a particle swarm optimizer used for designing combinational logic circuits. The scheme aims to distribute the search effort in a better way within the particles of the population as to accelerate convergence while improvin ..."
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In this paper, we introduce the use of a populationbased selection scheme in a particle swarm optimizer used for designing combinational logic circuits. The scheme aims to distribute the search effort in a better way within the particles of the population as to accelerate convergence while improving the robustness of the algorithm. For our study, we compare six PSObased approaches, combining different encodings (integer and binary) with both single and multiobjective selection schemes. The comparative study performed indicates that the use of a populationbased approach combined with an integer encoding improves both the robustness and quality of results of PSO when designing combinational logic circuits. 1