Recently several classical Genetic Algorithm principles have been challenged-including the Fundamental Theorem of Genetic Algorithms and the Principle of Minimal Alphabets. In addition, the recent No Free Lunch theorems raise further concerns. In this paper we review these issues and offer some new directions for GA researchers.

Quantum computers can exploit a Hilbert space whose dimension increases exponentially with the number of qubits. In experiment, quantum supremacy has recently been achieved by Google team using noisy intermediate-scale (NISQ) device over 50 However, question what be implemented on NISQ devices is still not fully explored, and discovering useful tasks for such topic considerable interest. Hybrid...

although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. this paper deals with scheduling jobs in lot streaming flexible flow line problems. the paper mathematically formulates the problem by a mixed integer linear programming model. this model solves small instances to optimality. moreo...

Evolutionary algorithms are heuristic techniques based on Darwinian model of evolutionary processes, which can be used to find approximate solutions of optimization and adaptation problems. Agent-based evolutionary algorithms are a result of merging two paradigms: evolutionary algorithms and multi-agent systems. In this paper agent-based evolutionary algorithm for solving well known Traveling S...

In this paper we discuss the possibilities of applying genetic algorithms (GA) for solving constraint satisfaction problems (CSP). We point out how the greediness of deterministic classical CSP solving techniques can be counterbalanced by the random mechanisms of GAs. We tested our ideas by running experiments on four diierent CSPs: N-queens, graph 3-colouring, the traac lights and the Zebra pr...

although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. but, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. this paper considers the problem of scheduling no-idle hybrid flow shops. a mixed integer linear programming model is first developed to mathematically form...

Genetic algorithms have been applied to a diverse field of problems with promising results. Using genetic algorithms modified to various degrees for tackling dynamic problems has attracted much attention in recent years. The main reason classical genetic algorithms do not perform well in such problems is that they converge and lose their genetic diversity. However, to be able to adapt to a chan...

Genetic Algorithms in Structure Design Sushil J. Louis Department of Computer Science Indiana University, Bloomington, IN 47405 [email protected] Gregory J. E. Rawlins Department of Computer Science Indiana University, Bloomington, IN 47405 [email protected] Abstract This paper considers the problem of using genetic algorithms to design structures. We relax one constraint on...

‎The most challenging task in dealing with Bayesian networks is learning their structure‎. ‎Two classical approaches are often used for learning Bayesian network structure;‎ ‎Constraint-Based method and Score-and-Search-Based one‎. ‎But neither the first nor the second one are completely satisfactory‎. ‎Therefore the heuristic search such as Genetic Alg...

The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved in the literature with heuristic techniques such as genetic algorithms and local search algorithms. In this paper we propose two approaches to attack the hardness of this problem. T...