A new algorithm, dubbed memory-based adaptive partitioning (MAP) of search space, which is intended to provide a better accuracy/speed ratio in the convergence of multi-objective evolutionary algorithms (MOEAs) is presented in this work. This algorithm works by performing an adaptive-probabilistic refinement of the search space, with no aggregation in objective space. This work investigated the...

logistics network is expected that opened facilities work continuously for a long time horizon without any failure; but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize cost of facility locations, customers’ assignment, and inventory management decisions when facilities face failure risks and doesn’t work. In our...

Optimal operation of multi-reservoir systems is one the most challenging problems in water resource management due to their multi-objective nature and time-consuming solving process. In this paper, Multi-Reservoir Parallel Cellular Automata-Simulated Annealing (MPCA-SA), a hybrid method based on cellular automata simulated annealing presented for bi-objective operations problems. The problem co...

Developing a reasonable and efficient emergency material scheduling plan is of great significance to decreasing casualties property losses. Real-world (EMS) problems are typically large-scale possess complex constraints. An evolutionary algorithm (EA) one the effective methods for solving EMS problems. However, existing EAs still face challenges when dealing with or equality To handle above cha...

Feature selection is a multi-objective problem with the two main conflicting objectives of minimising the number of features and maximising the classification performance. However, most existing feature selection algorithms are single objective and do not appropriately reflect the actual need. There are a small number of multi-objective feature selection algorithms, which are wrapper based and ...

In this research, a bi-objective scheduling problem with controllable processing times on identical parallel machines is investigated. The direction of this paper is mainly motivated by the adoption of the just-in-time (JIT) philosophy on identical parallel machines in terms of bi-objective approach, where the job processing times are controllable. The aim of this study is to simultaneously min...

Cloud federation enables service providers to collaborate provide better services customers. For cloud storage services, optimizing customer object placement for a member of is real challenge. Storage, migration, and latency costs need be considered. These are contradictory in some cases. In this article, we modeled as multi-objective optimization problem. The proposed model takes into account ...

An approach to construct multiple interpretable and precise fuzzy systems based on the Pareto Multi-objective Cooperative Coevolutionary Algorithm (PMOCCA) is proposed in this paper. First, a modified fuzzy clustering algorithm is used to construct antecedents of fuzzy system, and consequents are identified separately to reduce computational burden. Then, the PMOCCA and the interpretability-dri...

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MA...

In this paper, we consider the problem of rescheduling human resources in a battalion where new activities are assigned to the battalion by higher headquarters, requiring modification of an existing original schedule. The problem is modeled as a multi-criteria optimization problem with three objectives: (i) maximizing the number of tasks that are performed, (ii) minimizing the number of high-pr...