A combinatorial optimization problem, namely kMinimum Spanning Tree Problem, is to find a subtree with exactly k edges in an undirected graph G , such that the sum of edges’ weights is minimal. where graph G is made up of a set of vertices and weight attached edges. Since this problem is NP-hard, heuristic and metaheuristic methods are widely adopted for solving large instances. In this paper, ...

Computational cost of metaheuristic based optimum design algorithms grows excessively with structure size. This results in computational inefficiency of modern metaheuristic algorithms in tackling optimum design problems of large scale structural systems. This paper attempts to provide a computationally efficient optimization tool for optimum design of large scale steel frame structures to AISC...

This paper presents a hybrid metaheuristic approach (HMA) for solving the Unconstrained Binary Quadratic Programming (UBQP) problem. By incorporating a tabu search procedure into the framework of evolutionary algorithms, the proposed approach exhibits several distinguishing features, including a diversification-based combination operator and a distance-and-quality based replacement criterion fo...

The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for im...

In this paper, we present a new Artificial Bee Colony algorithm to solve the non-unicost Set Covering Problem. The Artificial Bee Colony algorithm is a recent metaheuristic technique based on the intelligent foraging behavior of honey bee swarm. Computational results show that Artificial Bee Colony algorithm is competitive in terms of solution quality with other metaheuristic approaches for the...

Design optimization of structures with discrete and continuous search spaces is a complex optimization problem with lots of local optima. Metaheuristic optimization algorithms, due to not requiring gradient information of the objective function, are efficient tools for solving these problems at a reasonable computational time. In this paper, the Doppler Effect-Mean Euclidian Distance Threshold ...

Dissolved oxygen (DO) concentration is an important water-quality parameter, and its estimation very for aquatic ecosystems, drinking water resources, agro-industrial activities. In the presented study, a new support vector machine (SVM) method, which improved by hybrid firefly algorithm–particle swarm optimization (FFAPSO), proposed accurate of DO. Daily pH, temperature (T), electrical conduct...

Research efforts in metaheuristics have shown that an intelligent incorporation of more classical optimization techniques in metaheuristics can be very beneficial. In this paper, we combine the metaheuristic ant colony optimization with dynamic programming for the application to the NP-hard k-cardinality tree problem. Given an undirected graph G with node and/or edge weights, the problem consis...

-The most important task in digital image processing is image segmentation. This paper put forward an unique image segmentation algorithm that make use of a Markov Random Field (MRF) hybrid with biologically inspired technique Bacteria Foraging Optimization Algorithm (BFOA) for Brain Magnetic Resonance Images The proposed new algorithm works on the image pixel data and a region/neighborhood map...