Search published articles


Showing 12 results for Distribution

Gh. Rahimi , Ar. Davoodinik ,
Volume 19, Issue 7 (8-2008)
Abstract

The intention of this study is the analysis of thermal behavior of functionally graded beam (FGB). The distribution of material properties is imitated exponential function. For thermal loading the steady state of heat conduction with exponentially and hyperbolic variations through the thickness of FGB, is considered. With comparing of thermal behavior of both isotropic beam and FGB, it is appea red that the quality of temperature distribution plays very important part in thermal resultant distribution of stresses and strains for FGB. So that, for detecting the particular thermal behavior of FGB, the function of heat distribution must be same as function of material properties distribution. In addition, In the case of exponential distribution of heat with no mechanical loads, in spite of the fact that the bending is accrued, the neutral surface does not come into existence.


E. Teimoury, I.g. Khondabi , M. Fathi ,
Volume 22, Issue 3 (9-2011)
Abstract

 

  Discrete facility location,

  Distribution center,

  Logistics,

  Inventory policy,

  Queueing theory,

  Markov processes,

The distribution center location problem is a crucial question for logistics decision makers. The optimization of these decisions needs careful attention to the fixed facility costs, inventory costs, transportation costs and customer responsiveness. In this paper we study the location selection of a distribution center which satisfies demands with a M/M/1 finite queueing system plus balking and reneging. The distribution center uses one for one inventory policy, where each arrival demand orders a unit of product to the distribution center and the distribution center refers this demand to its supplier. The matrix geometric method is applied to model the queueing system in order to obtain the steady-state probabilities and evaluate some performance measures. A cost model is developed to determine the best location for the distribution center and its optimal storage capacity and a numerical example is presented to determine the computability of the results derived in this study .


Maghsoud Amiri, Mehdi Seif Barghy, Laaya Olfat, Seyed Hossein Razavi Hajiagha ,
Volume 23, Issue 1 (3-2012)
Abstract

Inventory control is one of the most important issues in supply chain management. In this paper, a three-echelon production, distribution, inventory system composed of one producer, a set of wholesalers and retailers is considered. Costumers' demands can be approximated by a normal distribution and the inventory policy is a kind of continuous review (R, Q). In this paper, a model based on standard cost structure of inventory systems is developed and a heuristic algorithm is designed to optimize the developed model. The application of model is examined in a series of designed experiments that are compared with simulation results. These comparisons verify the validity of the model. Regarding to real complexities in three-echelon systems analysis, the proposed method can have a wide application in practical problems with the same considerations and assumptions. In addition, this method can be used to approximate those systems that follow a Poisson demand.
Fernando Antonio Moala,
Volume 25, Issue 4 (10-2014)
Abstract

The Weibull distribution has been widely used in survival and engineering reliability analysis. In life testing experiments is fairly common practice to terminate the experiment before all the items have failed, that means the data are censored. Thus, the main objective of this paper is to estimate the reliability function of the Weibull distribution with uncensored and censored data by using Bayesian estimation. Usually it is assigned prior distributions for the parameters (shape and scale) of the Weibull distribution. Instead, we assign prior distributions for the reliability function for a fixed time, that is, for the parameter of interest. For this, we propose different non-informative prior distributions for the reliability function and select the one that provides more accurate estimates. Some examples are introduced to illustrate the methodology and mainly to investigate the performance of the prior distributions proposed in the paper. The Bayesian analysis is conducted based on Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions

\"AWT


Seyed Mohammad Seyedhosseini, Mohammad Mahdavi Mazdeh, Dr. Ahmad Makui, Seyed Mohammad Ghoreyshi,
Volume 27, Issue 1 (3-2016)
Abstract

In any supply chain, distribution planning of products is of great importance to managers. With effective and flexible distribution planning, mangers can increase the efficiency of time, place, and delivery utility of whole supply chain. In this paper, inventory routing problem (IRP) is applied to distribution planning of perishable products in a supply chain. The studied supply chain is composed of two levels a supplier and customers. Customers’ locations are geographically around the supplier location and their demands are uncertain and follow an independent probability distribution functions. The product has pre-determined fixed life and is to be distributed among customers via a fleet of homogenous vehicles. The supplier uses direct routes for delivering products to customers. The objective is to determine when to deliver to each customer, how much to deliver to them, and how to assign them to vehicle and routes. The mentioned problem is formulated and solved using a stochastic dynamic programming approach. Also, a numerical example is given to illustrate the applicability of proposed approach.


Morteza Rasti-Barzoki, Ali Kourank Beheshti, Seyed Reza Hejazi,
Volume 27, Issue 2 (6-2016)
Abstract

This paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. We assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. In this paper, we present an Artificial Immune System (AIS) for this problem. The objective is to minimize the sum of the total weighted number of tardy jobs and the batch delivery costs. A batch setup time has to be added before processing the first job in each batch. Using computational test, we compare our method with an existing method for the mentioned problem in literature namely Simulated Annealing (SA). Computational tests show the significant improvement of AIS over the SA.


Ebrahim Teimoury, Farshad Saeedi, Ahmad Makui,
Volume 28, Issue 1 (3-2017)
Abstract

Recently, urbanization has been expanded rapidly in the world and a number of metropolitan areas have been appeared with a population of more than 10 million people. Because of dense population in metropolitan and consequently increasing the delivery of goods and services, there has been a lot of problems including traffic congestion, air pollution, accidents and high energy consumption. This made some complexities in distribution of urban goods; Therefore, it is essential to provide creative solutions to overcome these complexities. City logistics models can be effective in solving these complexities.

In this paper, concepts and definitions related to city logistics are explained to provide a mathematical model in order to design city logistics distribution network aim at minimizing response times. This objective is effective for goods and emergency services, especially in times of crisis and also for goods that are delivered as soon as possible. This is a three-level network and has been used in modeling of queuing theory. To validate the model, a numerical example has been established and results of the model have been explained using BARON solver in Gams software. Finally, conclusions and recommendations for future research are presented.


Zahra Karimi Ezmareh, Gholam Hossein Yari,
Volume 30, Issue 2 (6-2019)
Abstract

In this paper, a new distribution that is highly applicable in the fields of reliability and economics is introduced. Also the parameters of this distribution is estimated using two methods of Maximum Likelihood and Bayes with two prior distributions Weibull and Uniform, and these two methods are compared using Monte-Carlo simulation. Finally, this new model is fit on the real data(with the failure time of 84 aircraft) and some of comparative criteria are calculated to confirm superiority of the proposed model compared to other models.
Amir-Mohammad Golmohammadi, Mahboobeh Honarvar, Guangdong Guangdong, Hasan Hosseini-Nasab,
Volume 30, Issue 4 (12-2019)
Abstract

There is still a great deal of attention in cellular manufacturing systems and proposing capable metaheuristics to better solve these complicated optimization models. In this study, machines are considered unreliable that life span of them follows a Weibull distribution. The intra and inter-cell movements for both parts and machines are determined using batch sizes for transferring parts are related to the distance traveled through a rectilinear distance. The objectives minimize the total cost of parts relocations and maximize the processing routes reliability due to alternative process routing. To solve the proposed problem, Genetic Algorithm (GA) and two recent nature-inspired algorithms including Keshtel Algorithm (KA) and Red Deer Algorithm (RDA) are employed. In addition, the main innovation of this paper is to propose a novel hybrid metaheuristic algorithm based on the benefits of aforementioned algorithms. Some numerical instances are defined and solved by the proposed algorithms and also validated by the outputs of exact solver. A real case study is also utilized to validate the proposed solution and modeling algorithms. The results indicate that the proposed hybrid algorithm is more appropriate than the exact solver and outperforms the performance of individual ones.
Hamiden Khalifa, E. E. Ammar,
Volume 31, Issue 1 (3-2020)
Abstract

   This paper deals with a multi- objective linear fractional programming problem involving probabilistic parameters in the right- hand side of the constraints. These probabilistic parameters are randomly distributed with known means and variances through the use of Uniform and Exponential Distributions. After converting the probabilistic problem into an equivalent deterministic problem, a fuzzy programming approach is applied by defining a membership function. A linear membership function is being used for obtaining an optimal compromise solution. The stability set of the first kind without differentiability corresponding to the obtained optimal compromise solution is determined. A solution procedure for obtaining an optimal compromise solution and the stability set of the first kind is presented. Finally, a numerical example is given to clarify the practically and the efficiency of the study.
 
Rezvan Rezaei, Gholam Hossein Yari, Zahra Karimi Ezmareh,
Volume 31, Issue 3 (9-2020)
Abstract

In this paper, a new five-parameter distribution is proposed that is called MarshallOlkin Gompertz Makeham distribution(MOGM). This new model is applicable in analysis lifetime data, engineering and actuarial. In this research, some properties of the new model such as mode, moment, Reyni entropy, Tsallis entropy, quantile function and the hazard rate function which is decreasing and unimodal, are studied. The unknown parameters of the MOGM distribution are estimated using the maximum likelihood and Bayes methods. Then these methods are compared using Monte Carlo simulation and the best estimator is proposed. Finally, applications of the proposed model are illustrated to show its usefulness.
Zahra Karimi Ezmareh, Gholamhossein Yari,
Volume 33, Issue 4 (12-2022)
Abstract

‎Recently, generalized distributions have received much attention due to their high applicability and flexibility. This paper introduces a new five-parameter distribution called Kumaraswamy-G generalized Gompertz distribution, which is widely used in the field of survival and lifetime data. In introducing a new distribution, it is important to study the statistical properties and the estimation of its parameters. Therefore, this paper studies the statistical properties of this new distribution. In addition, the parameters of this distribution are estimated by three methods. Finally, using a real dataset, the performance of the introduced distribution is investigated.


Page 1 from 1