The ongoing container shortage crisis has presented significant challenges for the freight forwarding industry, requiring companies to implement adaptive measures in order maintain peak operational efficiency. This article presents a novel mathematical model and artificial bee colony algorithm (ABC) with Pareto-based approach solve single-container-loading problems. goal is fit set of boxes str...

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...

In this study, solutions for machinery layout with the aim of reducing transportation costs will be discussed. To do this, imperialist competitive algorithm (ICA), which is a very complicated and effective meta-heuristic algorithm is introduced. In the offered algorithm, different kinds of machinery layout are considered in single-row as country and then the best possible layout is developed ba...

Nowadays, in majority of academic contexts, it has been tried to consider the highest possible level of similarities to the real world. Hence, most of the problems have complicated structures. Traditional methods for solving almost all of the mathematical and optimization problems are inefficient. As a result, meta-heuristic algorithms have been employed increasingly during recent years. In thi...

This paper presents a new mathematical model for integrated dynamic cellular manufacturing systems and production planning that minimizes machine purchasing, intra-cell material handling, cell reconfiguration and setup costs. The presented model forms the manufacturing cells and determines the quantity of machine and movements  during each period of time. This problem is NP-hard, so a meta-heur...

Multi-objective problems are a category of optimization problem that contains more than one objective function and these objective functions must be optimized simultaneously. Should the objective functions be conflicting, then a set of solutions instead of a single solution is required. This set is known as Pareto optimal. Multi-objective optimization problems arise in many real world applicati...

optimal sitting and sizing of shunt capacitor banks at the distribution networks for the purpose of power quality improvement is drawn much attention of electric power utilities in the last decades. determining the optimal number, location and sizing of capacitor using bee colony optimization algorithm (bco) is being presented in this paper. the bco algorithm is a new population based meta-heur...

Distributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user...

Node cooperation can protect wireless networks from eavesdropping by using the physical characteristics of wireless channels rather than cryptographic methods. Allocating the proper amount of power to cooperative nodes is a challenging task. In this paper, we use three cooperative nodes, one as relay to increase throughput at the destination and two friendly jammers to degrade eavesdropper&rsqu...

in this paper, a stochastic multi-depot multi-objective vehicle routing problem (vrp) is studied. based on observations in real-world problems, we develop an aspect of the problem, such as stochastic availability of routes. to solve the problem in this situation, a two-objective mathematical model is developed, in which the related objective functions are: (1) minimizing transportation costs an...