This research present a set-partitioning heuristic to generate populations in a hybrid genetic algorithm (hGA) which is able to solve four different variants of the vehicle routing problem: the multi-depot vehicle routing problem (MDVRP), the heterogeneous fleet and mix decisions (type, size and number of vehicle) (HFMVRP), site dependent vehicle routing problem (SDVRP) and the asymmetric vehic...

To enhance the e fficien cy of corporation cooperative p artner se le ct io n and o ptimization p roce ss in virtual corporations, a Hybrid genetic algorithm (HG A) and its application in cooperative partner sele ct io n process and optimizations model for was presented. In the model, the hybrid genetic algorithm is used t o enhance the efficiency of corporation cooperative partner select io n ...

The Maximum Clique Problem (MCP) has been studied for decades and is well known in graph theory as a problem that is difficult as it as it is known to be NP-complete. The MCP has a vast domain of application such as finance, biochemistry, bioinformatics, and many more. Many niching methods have been successfully applied in Genetic Algorithms (GA) to diversify the population and avoid getting tr...

In the paper, we give illustrated reviews, new approaches and results of how rcps –problems are being solved with Hybrid algorithm’s. Firstly, considering Hybrid Genetic Algorithm (HGA), Vicente a et al 2007, introducing many changes in Genetic algorithm (GA) paradigm, resulting in HGA giving fast and high quality algorithms out performing state-of-the-art-algorithm (SOTAA). for rcps-problem. S...

This paper aims to build integrated forward and reverse logistics model, and to optimize it with closed loop supply chain (CLSC). After that, we evaluate the effectiveness of the proposed model with the numerical examples, and simulate it with a bottles distilling/sale company in Korea. This paper designs the method of calculation for a solution using optimization algorithms with the priority-b...

In this paper, an advanced novel heuristic algorithm is presented, the hybrid genetic algorithm with neural networks (HGA-NN), which is used to identify an optimum feature subset and to increase the classification accuracy and scalability in credit risk assessment. This algorithm is based on the following basic hypothesis: the high-dimensional input feature space can be preliminarily restricted...

In this paper, we propose a hybrid genetic algorithm with fuzzy logic controller (flc-hGA) to solve the resource-constrained multiple project scheduling problem (rc-mPSP) which is well known NP-hard problem. Objectives described in this paper are to minimize total project time and to minimize total tardiness penalty. However, it is difficult to treat the rc-mPSP problems with traditional optimi...

Task scheduling for the cloud is one of main advances in IoMT stage, which impacts whole execution resource. Cloud a proficient headway computation, and it encompasses data storage, management, manipulation large volumes. Thus, proposition being made better approach to proffer task cloud. In this case, new hybrid genetic algorithm (HGA) proposed. The proposed HGA method will be justified by con...

In this paper, the approach focused on the variables involved in assessing the quality of a distributed generation system are reviewed in detail, for its investigation and research contribution. The aim to minimize the electric power losses (unused power consumption) and optimize the voltage profile for the power system under investigation. To provide this assessment, several experiments have b...

In this paper a variable’s involved in assessing the quality of a distributed generation system are reviewed, aiming to minimize the electric power losses (unused power consumption) and optimize the voltage profile. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple DG units. The possibility and ...