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This paper presents an encoding technique that is common for many different logic synthesis problems. It enables us to construct a system of Boolean functions, and then to decompose this system into sub-systems in such a...

Determining an optimal schedule to minimize the completion time of the last job abandoning the system (makespan) becomes a very difficult problem when there are more than two machines in the flow shop. Due both to its ec...

This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to the traveling salesman problem (TSP). In the ACS, a set of cooperating agents called ants cooperate to find good solutions to ...

Over the past few years, a continually increasing number of research efforts have investigated the application of evolutionary computation techniques for the solution of scheduling problems. Scheduling problems can pose...

Allocation of the components (tasks) of a parallel program to processors in a multiprocessor or a multicomputer system take full advantage of the computational power provided by the system. Evolutionary approaches has b...

Over the past three decades extensive search have been done on pure m-machine flow shop problems. Many researchers faced the Flow Shop Scheduling Problem (FSSP) by means of well-known heuristics which, are successfully ...

The travelling salesman problem (TSP) is a NP-hard problem. Techniques as either Branch and Bound or Dynamic Programming supplied the global optimum solution for instances with more than 7000 cities. But, ther needed mor...

Scheduling is an active area of research in applied artificial intelligence. Scheduling problems typically comprise several concurrent (and often conflicting) goals, and several resources which may be allocated in order ...

This work summarizes results when facing the problem of allocating a number of nonidentical tasks in a parallel system. The model assumes that the system consists of a number of identical processors and that only one tas...

Determining an optimal schedule to m1mm1ze the completion time of the last job abandoning the system (makespan) become a very difficult problem when there are more than two machines in the flow shop. Due both to its econ...

This paper evaluates the application of the computational intelligence methodologies in a nonlinear process identification. The different intelligent methodologies utilized are evolutionary computation (hybrid genetic al...

The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm. Benchmark test...

This work studies the solution space topology of the Traveling Salesman Problem or TSP, as a bi-objective optimization problem. The concepts of category and range of a solution are introduced for the first time in this ...

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describe...

The rapid proliferation of Learning Management Systems (LMS) in K–12 education has generated a substantial body of research, yet how its core themes emerge, converge, and transform over time remains insufficiently unde...

Abstract Background Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of simultaneously optimizing multiple, often conflicting objectives....

Abstract Intertidal macrobenthos are vital bioindicators of coastal ecosystem health due to their ecological roles, limited mobility, and sensitivity to environmental disturbances. However, traditional field‐based moni...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

This paper proposes an innovative automated multiphysics Microelectromechanical systems (MEMS) co-optimization platform integrating the embedded reduced-order modeling offered by Coventor MEMS+ with MATLAB’s numerical ...

The development goal of artificial intelligence is to enable machines to think and act like humans, solving complex problems, and more importantly, interacting effectively in a complex, dynamic, and uncertain physical wo...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

Cytochrome P450cam(CYP101A1) catalyzes the hydroxylation of d-camphor by molecular oxygen. The enzyme-catalyzed hydroxylation exhibits a high degree of regioselectivity and stereoselectivity, with a single major product,...

Recent advances in protein structure prediction, such as AlphaFold, have demonstrated the power of deep neural architectures like the Evoformer for capturing complex spatial and evolutionary constraints on protein confor...

Abstract Dissecting the functional impact of genetic mutations is essential to advancing our understanding of genotype-phenotype relationships and identifying therapeutic targets. Despite progress in sequencing and genom...