scholarly journals A Robust Approach to CCRM Interval Regression considering Interval Coincidence Degree

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Wang Yu ◽  
Yan Shilin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Programming Model ◽  
Coincidence Degree ◽  
Nonlinear Regression Model ◽  
Robust Approach ◽  
Average Ratio ◽  
Proposed Model ◽  
Nonlinear Programming Model ◽  
Fitting Accuracy

Traditional CCRMs (Constrained Center-and-Range Methods) in solving the problem of interval regression could hardly make tradeoffs between the overall fitting accuracy and the coincidence degree between the observed and predicted intervals and could also hardly reduce the number of disjoint elements between the observed and predicted intervals, as well as raise the average ratio of all predicted intervals contained within their observed intervals. This paper constructed a nonlinear regression model based on center-and-range method, in which the maximization of coincidence degree for the sample with the worst coincidence degree between the observed and predicted interval was incorporated into the traditional CCRM model’s objective. This novel nonlinear programming model was proven to be a convex one that satisfied K-T condition. Monte Carlo simulation shows that the model is degenerated to the compared CCRM+ model as the objective only contains the minimization of the overall fitting accuracy for both center and range sample series. In this situation, it could obtain a better solution than the use of the compared CCRM model. In addition, when the proposed model only takes into account the maximization of coincidence degree for the sample with the worst coincidence degree between the observed and predicted interval, the model shows a better performance than the CCRM+ model in terms of the average ratio of all predicted intervals contained within their observed intervals, as well as the average number of forecasts with 0% accuracy.

scholarly journals An Improved Model for Evaluating Change in Randomized Pretest, Posttest, Follow-Up Designs

Methodology ◽  
2012 ◽  
Vol 8 (3) ◽  
pp. 97-103 ◽  
Author(s):  
Constance A. Mara ◽  
Robert A. Cribbie ◽  
David B. Flora ◽  
Cathy LaBrish ◽  
Laura Mills ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Group Differences ◽  
Primary Research ◽  
Control Groups ◽  
Proposed Model ◽  
Research Questions ◽  
Improved Model ◽  
And Control

Randomized pretest, posttest, follow-up (RPPF) designs are often used for evaluating the effectiveness of an intervention. These designs typically address two primary research questions: (1) Do the treatment and control groups differ in the amount of change from pretest to posttest? and (2) Do the treatment and control groups differ in the amount of change from posttest to follow-up? This study presents a model for answering these questions and compares it to recently proposed models for analyzing RPPF designs due to Mun, von Eye, and White (2009) using Monte Carlo simulation. The proposed model provides increased power over previous models for evaluating group differences in RPPF designs.

A Bi-objective Multi-Product Multi-Constraint EPQ Model in a Stochastic Environment and Partial Shortage

2020 ◽  
Vol 19 (03) ◽  
pp. 567-587
Author(s):  
Seyedeh Sanaz Mirkhorsandi ◽  
Seyed Hamid Reza Pasandideh
Keyword(s):  
Goal Attainment ◽  
Programming Model ◽  
Multi Objective ◽  
Holding Costs ◽  
Inventory Costs ◽  
Economic Production ◽  
Proposed Model ◽  
Demand Rate ◽  
Nonlinear Programming Model ◽  
Epq Model

One of the classical models for inventory control is economic production quantity (EPQ), which is widely used in industry. In this paper, an EPQ model with partial shortage is developed by considering the real world conditions, and costs related to the backorder demand are taken as fixed and time-dependent. In the proposed model, determination of the inventory cycle length, the length of positive inventory cycle and backordered demand rate are considered in shortage period. The aim of the presented research is to minimize the total inventory costs and the space required for storage products so that the stochastic and classic constraints including holding costs, lost sales, backorder, budget, total number of productions and average shortage times should be satisfied while optimizing the multi-objective problem. Presented model is a bi-objective nonlinear programming model. Then, to solve the proposed model, three multi-objective decision-making methods including Lp-metric, goal programming and goal attainment are used. Besides, numerical examples are executed in small, medium and large scales by use of GAMS software, and the performance of the methods is compared in terms of objective functions and required CPU time. Finally, sensitivity analysis is done to determine the effect of change in the main parameters of the model on the objective function value.

Monte Carlo Simulation of Seebeck Coefficient and Electrical Conductivity in Thermoelectrics

2013 ◽  
Vol 709 ◽  
pp. 176-179 ◽  
Author(s):  
Jian Li
Keyword(s):  
Electrical Conductivity ◽  
Monte Carlo Simulation ◽  
Grain Size ◽  
Monte Carlo ◽  
Seebeck Coefficient ◽  
Ground State ◽  
Proposed Model ◽  
Average Grain Size ◽  
Polycrystalline Ceramics ◽  
Simulation Results

we proposed a scheme for simulating the electronic and thermoelectric properties of polycrystalline ceramics. The simulation results show that the ground state electrons are easily confined in the largest grain. In addition, with the increasing average grain size, the Seebeck coefficient decreases while the electrical conductivity increases monotonically. The simulation results agree well with the available experimental results. Therefore, the proposed model is proved to be a promising approach for thermoelectric investigations.

scholarly journals Median location problem with two probabilistic line barriers: Extending the Hook and Jeeves algorithm

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Saber Shiripour ◽  
Nezam Mahdavi-Amiri
Keyword(s):  
Location Problem ◽  
Programming Model ◽  
Distance Functions ◽  
Mixed Integer ◽  
Lower And Upper Bounds ◽  
Rectilinear Distance ◽  
Proposed Model ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model ◽  
New Facility

<p style='text-indent:20px;'>We consider a median location problem in the presence of two probabilistic line barriers on the plane under rectilinear distance. It is assumed that the two line barriers move on their corresponding horizontal routes uniformly. We first investigate different scenarios for the position of the line barriers on the plane and their corresponding routes, and then define the visibility and invisibility conditions along with their corresponding expected barrier distance functions. The proposed problem is formulated as a mixed-integer nonlinear programming model. Our aim is to locate a new facility on the plane so that the total weighted expected rectilinear barrier distance is minimized. We present efficient lower and upper bounds using the forbidden location problem for the proposed problem. To solve the proposed model, the Hooke and Jeeves algorithm (HJA) is extended. We investigate various sample problems to test the performance of the proposed algorithm and appropriateness of the bounds. Also, an empirical study in Kingston-upon-Thames, England, is conducted to illustrate the behavior and applicability of the proposed model.</p>

scholarly journals Integrated Optimization on Assortment Packing and Collaborative Shipping for Fashion Clothing

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qianying Wang ◽  
Yiping Jiang ◽  
Yang Liu
Keyword(s):  
Numerical Experiments ◽  
Optimization Problem ◽  
Programming Model ◽  
Social Resources ◽  
Mixed Integer ◽  
Integrated Optimization ◽  
Proposed Model ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model ◽  
Effectiveness And Efficiency

With the diversification of customer’s demand and the shortage of social resources, meeting diverse requirements of customers and reducing logistics costs have attracted great attention in logistics area. In this paper, we address an integrated optimization problem that combines fashion clothing assortment packing with collaborative shipping simultaneously. We formulate this problem as a mixed integer nonlinear programming model (MINLP) and then convert the proposed model into a simplified model. We use LINGO 11.0 to solve the transformed model. Numerical experiments have been conducted to verify the effectiveness and efficiency of the proposed model, and the numerical results show that the proposed model is beneficial to the fashion clothing assortment packing and collaborative shipping planning.

scholarly journals An open source tool for reliability evaluation of distribution system using Monte Carlo simulation

2019 ◽  
Vol 14 (3) ◽  
pp. 1065
Author(s):  
Bhargava Chitumodhu ◽  
Renuka Loka
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Integration ◽  
Distribution System ◽  
Web Application ◽  
Data Exchange ◽  
Electrical Energy ◽  
Reliability Evaluation ◽  
Proposed Model ◽  
System Data

<span lang="EN-US">As the demand for electricity is shooting exponentially, reliable supply of electrical energy from generation to customer is the challenging task faced by utilities. Though generation and transmission can be maintained at hundred percent reliability, reliability of entire system cannot be assured unless focus is laid on distribution system. Most of the faults are occurring on the distribution system which is directly connected to different customers. Hence, we need to intensify the attention at distribution level. Due to deregulation, private players are evolving in distribution sector which complicates power system data exchange and information integration.   To cope with this scenario, reliability evaluation of distribution system through Monte Carlo Simulation (MCS) with feature of interoperability for Bus 2 of RBTS system has been introduced and analyzed using SOAP web services. Simulation is performed by developing a web application in Java and is deployed on the Glass-fish server using JAX-WS. The intent behind this proposed model is to use the internet as the transactional tool and exposing the functionality of the program for reliability evaluation for utilities to use and providing facility of interoperability through standards refinement and integration into profiles.</span>

scholarly journals Modeling Prices of Islamic Commodity Swaption

2018 ◽  
Vol 31 (2) ◽  
pp. 111-131
Author(s):  
Nahla Ghazi Aljudaibi Nahla Ghazi Aljudaibi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Intrinsic Value ◽  
Pricing Model ◽  
Proposed Model ◽  
Risk Free Rate ◽  
Positive Effect ◽  
Free Rate

Derivatives that manage commodity risk over multiple periods are not Sharīʿah-compliant. This study proposes a Sharīʿah-compliant swaption model (waʿdān or two promises on swap) for hedging commodity risk. The model combines two separate and independent waʿds (waʿdān) on commodity swap through murābaḥah contract. Black (1976) model is used to determine the intrinsic value for the counter-parties involved in the contract. The risk-free rate is replaced with the return on AAA ṣukūk to make Black (1976) model Sharīʿah compliant. The proposed Sharīʿah-compliant model is compared with the conventional swaption model, and with the Islamic commodity option (waʿdān on commodity) for its effectiveness. The tests of the model show that the proposed Islamic pricing model has a higher positive effect than the conventional swaption model. In addition, the proposed Islamic commodity swaption is more efficient than Islamic commodity options. The reliability of the proposed model was established by the Monte Carlo simulation run with 10,000 iterations.

scholarly journals Routing cross-docking depots, considering the time windows and pricing routes (case study: container transportation of Chabahar port)

2020 ◽  
Vol 33 (02) ◽  
pp. 409-422
Author(s):  
Farhad Bavar ◽  
Majid Sabzehparvar ◽  
Mona Ahmadi Rad
Keyword(s):  
High Efficiency ◽  
Programming Model ◽  
Time Windows ◽  
Container Transportation ◽  
Total Cost ◽  
Cross Docking ◽  
Proposed Model ◽  
Nonlinear Programming Model ◽  
Implementation Time ◽  
The Cost

In this study, we develop a model for routing cross-docking centers considering time windows and pricing routs. In this model picking and delivery in several times is permitted and each knot can be serviced by more than one vehicle. Every truck can transport one or more product, in other words, we consider compatibility between product and vehicle. This model includes two goals: reducing the total cost and reducing the cost of carrying goods (freight fare). The total cost includes the cost required to traverse between the points, the cost of traversing the routes between the central cross-docking center and the first points after moving, and the cost to traverse the routes between the last points in each route and the depots that must be minimized. In general, the purpose of the model is to obtain the number of cross-docking center, the number of vehicles and the best route in the distribution network. We present a nonlinear programming model for this problem. We have solved the proposed model by GAMS. As the dimensions of the problem increase, the implementation time of the program increases progressively. So, in order to solve the model in medium and large scales, we proposed a genetic meta-heuristic algorithm. The results of examining different issues by the meta-heuristic approach show the very high efficiency of the developed algorithms in terms of the solution time and the answer of the problem.

scholarly journals A hybrid NSGA-II algorithm for the closed-loop supply chain network design in e-commerce  

2021 ◽  
Author(s):  
Shayan Shafiee Moghadam ◽  
Amir Aghsami ◽  
Masoud Rabbani
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Programming Model ◽  
Mixed Integer ◽  
Modern World ◽  
Supply Chain Network ◽  
Nsga Ii ◽  
Closed Loop Supply Chain ◽  
Proposed Model ◽  
Nonlinear Programming Model

Designing the supply chain network is one of the significant areas in e-commerce business management. This concept plays a crucial role in e-commerce systems. For example, location-inventory-pricing-routing of an e-commerce supply chain is considered a crucial issue in this field. This field established many severe challenges in the modern world, like maintaining the supply chain for returned items, preserving customers' trust and satisfaction, and developing an applicable supply chain with cost considerations. The research proposes a multi-objective mixed integer nonlinear programming model to design a closed-loop supply chain network based on the e-commerce context. The proposed model incorporates two objectives that optimize the business's total profits and the customers' satisfaction. Then, numerous numerical examples are generated and solved using the epsilon constraint method in GAMS optimization software. The validation of the given model has been tested for the large problems via a hybrid two-level non-dominated sort genetic algorithm. Finally, some sensitivity analysis has been performed to provide some managerial insights.

scholarly journals Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

2015 ◽  
Vol 371 ◽  
pp. 65-68
Author(s):  
S. Kim ◽  
W. Nam ◽  
H. Ahn ◽  
T. Kim ◽  
J.-H. Heo
Keyword(s):  
Climate Change ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Frequency Analysis ◽  
Logistic Models ◽  
Time Dependent ◽  
Threshold Data ◽  
Proposed Model ◽  
Hydrologic Data ◽  
Peak Over Threshold

Abstract. Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold) data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.

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