Today, there is a high number of injuries and various wastes and debris produced during natural and unnatural events. This study aims to investigate the reverse logistics planning problem in the response and reaction phases as well as improvement and reconstruction in earthquake conditions by using a real case study. Regarding the high complexity of this type of optimization problem, a multi-ob...

distribution centers (dcs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.this paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. an evolutionary algorithm named non-dominated sorting ant colony optimization (nsaco) is used as the optimi...

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several mult...

the vehicle driving comfort has become one of the important factors of vehicle quality and receives increasing attention. in this paper, optimal points of vehicle suspension parameters are generated using modified non-dominated sorting genetic algorithm (nsga-ii) for pareto optimization of 5-degree of freedom vehicle vibration model considering three conflicting functions simultaneously. in thi...

In this study a supply chain network design model has been developed considering both forward and reverse flows through the supply chain. Total Cost, environmental factors such as CO2 emission, and social factors such as employment and fairness in providing job opportunities are considered in three separate objective functions. The model seeks to optimize the facility location proble...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

In this paper, a multi-objective reconfiguration problem has been solved simultaneously by a modified ant colony optimization algorithm. Two objective functions, real power loss and energy not supplied index (ENS), were utilized. Multi-objective modified ant colony optimization algorithm has been generated by adding non-dominated sorting technique and changing the pheromone updating rule of ori...

This study addresses the pickup and delivery problem for cross-docking strategy, in which shipments are allowed to be transferred from suppliers to retailers directly as well as through cross-docks. Usual models that investigate vehicle routing in cross-docking networks force all vehicles to stop at the cross-dock even if a shipment is about to a full truckload or the vehicle collects and deliv...

A new model and solution for the energy minimizing vehicle routing problem with time windows (EVRPTW) and customers’ priority is presented in this paper. In this paper unlike prior attempts to minimize cost by minimizing overall traveling distance, the model also incorporates energy minimizing which meets the latest requirements of green logistics. This paper includes the vehicles load as an ad...

In this paper, we propose an efficient approach to design optimization of analog circuits that is based on the reinforcement learning method. In this work, Multi-Objective Learning Automata (MOLA) is used to design a two-stage CMOS operational amplifier (op-amp) in 0.25μm technology. The aim is optimizing power consumption and area so as to achieve minimum Total Optimality Index (TOI), as a new...