scholarly journals The Modified Rural Postman Problem in Vehicle Route Optimization

2018 ◽  
Vol 20 (3) ◽  
pp. 88-92
Author(s):  
Petr Kozel ◽  
Lucie Orlikova ◽  
Sarka Michalcova
Keyword(s):  
Linear Programming ◽  
Real Life ◽  
Transport Network ◽  
Route Optimization ◽  
Network Services ◽  
Rural Postman Problem ◽  
Life Problems ◽  
Strongly Connected ◽  
Service Vehicles ◽  
Strongly Connected Network

The submitted paper deals with designing routes of the vehicles, which provide the transport network services. We limit our focus to such tasks, where the priority is the edge service in the transport network and the initial problem is finding an Eulerian path. Regarding to real-life problems, this contribution presents such procedure of solving, which takes into account both the existence of a mixed transport network containing one-way roads and the existence of a wider transport network. In this network, there are only selected edges with possibility of the effective passages. This problem can be solved by the modified Rural Postman Problem assuming the strongly connected network. Linear programming is a suitable tool for designing optimal routes of service vehicles.

scholarly journals Connectivity Indices of Intuitionistic Fuzzy Graphs and Their Applications in Internet Routing and Transport Network Flow

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Tulat Naeem ◽  
Abdu Gumaei ◽  
Muhammad Kamran Jamil ◽  
Ahmed Alsanad ◽  
Kifayat Ullah
Keyword(s):  
Network Flow ◽  
Real Life ◽  
Vital Role ◽  
Transport Network ◽  
Internet Routing ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Graphs ◽  
Life Problems ◽  
Connectivity Indices ◽  
Intuitionistic Fuzzy Graphs

Connectivity index CI has a vital role in real-world problems especially in Internet routing and transport network flow. Intuitionistic fuzzy graphs IFGs allow to describe two aspects of information using membership and nonmembership degrees under uncertainties. Keeping in view the importance of CI s in real life problems and comprehension of IFGs , we aim to develop some CI s in the environment of IFGs . We introduce two types of CI s , namely, CI and average CI , in the frame of IFGs . In spite of that, certain kinds of nodes called IF connectivity enhancing node IFCEN , IF connectivity reducing node IFCRN , and IF neutral node are introduced for IFGs . We have introduced strongest strong cycles, θ -evaluation of vertices, cycle connectivity, and CI of strong cycle. Applications of the CI s in two different types of networks are done, Internet routing and transport network flow, followed by examples to show the applicability of the proposed work.

scholarly journals A guide to conic optimisation and its applications

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1087-1106
Author(s):  
Adam N. Letchford ◽  
Andrew J. Parkes
Keyword(s):  
Linear Programming ◽  
Real Life ◽  
Life Problems ◽  
Insight Into ◽  
The Way

Most OR academics and practitioners are familiar with linear programming (LP) and its applications. Many are however unaware of conic optimisation, which is a powerful generalisation of LP, with a prodigious array of important real-life applications. In this invited paper, we give a gentle introduction to conic optimisation, followed by a survey of applications in OR and related areas. Along the way, we try to help the reader develop insight into the strengths and limitations of conic optimisation as a tool for solving real-life problems.

A Two-Fold Linear Programming Model with Fuzzy Data

2012 ◽  
Vol 2 (3) ◽  
pp. 1-12 ◽  
Author(s):  
Saber Saati ◽  
Adel Hatami-Marbini ◽  
Madjid Tavana ◽  
Elham Hajiahkondi
Keyword(s):  
Linear Programming ◽  
Optimization Problems ◽  
Programming Model ◽  
Optimization Technique ◽  
Real Life ◽  
Optimal Solutions ◽  
Lack Of Information ◽  
Life Problems ◽  
Fuzzy Ranking ◽  
Lp Model

Linear programming (LP) is the most widely used optimization technique for solving real-life problems because of its simplicity and efficiency. Although LP models require well-suited information and precise data, managers and decision makers dealing with optimization problems often have a lack of information on the exact values of some parameters used in their models. Fuzzy sets provide a powerful tool for dealing with this kind of imprecise, vague, uncertain or incomplete data. In this paper, the authors propose a two-fold model which consists of two new methods for solving fuzzy LP (FLP) problems in which the variables and the coefficients of the constraints are characterized by fuzzy numbers. In the first method, the authors transform their FLP model into a conventional LP model by using a new fuzzy ranking method and introducing a new supplementary variable to obtain the fuzzy and crisp optimal solutions simultaneously with a single LP model. In the second method, the authors propose a LP model with crisp variables for identifying the crisp optimal solutions. The authors demonstrate the details of the proposed method with two numerical examples.

Transportation Problem in Neutrosophic Environment

2020 ◽  
pp. 180-212 ◽  
Author(s):  
Jayanta Pratihar ◽  
Ranjan Kumar ◽  
Arindam Dey ◽  
Said Broumi
Keyword(s):  
Linear Programming ◽  
Fuzzy Set ◽  
Transportation Problem ◽  
Intuitionistic Fuzzy Set ◽  
Real Life ◽  
Neutrosophic Set ◽  
Neutrosophic Sets ◽  
North West ◽  
Life Problems ◽  
The Cost

The transportation problem (TP) is popular in operation research due to its versatile applications in real life. Uncertainty exists in most of the real-life problems, which cause it laborious to find the cost (supply/demand) exactly. The fuzzy set is the well-known field for handling the uncertainty but has some limitations. For that reason, in this chapter introduces another set of values called neutrosophic set. It is a generalization of crisp sets, fuzzy set, and intuitionistic fuzzy set, which is handle the uncertain, unpredictable, and insufficient information in real-life problem. Here consider some neutrosophic sets of values for supply, demand, and cell cost. In this chapter, extension of linear programming principle, extension of north west principle, extension of Vogel's approximation method (VAM) principle, and extended principle of MODI method are used for solving the TP with neutrosophic environment called neutrosophic transportation problem (NTP), and these methods are compared using neutrosophic sets of value as well as a combination of neutrosophic and crisp value for analyzing the every real-life uncertain situation.

Metaheuristic Approaches for Vehicle Routing Problems

2013 ◽  
Vol 6 (2) ◽  
pp. 17-32 ◽  
Author(s):  
M. Saravanan ◽  
K.A.Sundararaman
Keyword(s):  
Vehicle Routing ◽  
Real Life ◽  
Distribution Networks ◽  
Routing Problem ◽  
Goods And Services ◽  
Life Problems ◽  
Side Constraints ◽  
Service Vehicles ◽  
Annealing Algorithms

Routing of service vehicles are the heart of many service operations. Exclusively vehicle routing problem (VRP) plays a central role in the optimization of distribution networks. The routing of service vehicles has a major impact on the quality of the service provided. In distribution of goods and services, it is time and again required to determine a combination of least cost vehicle routes through a set of geographically scattered customers, subject to side constraints. The case most commonly studied is where all vehicles are identical. Due to the complexity involved in solving the VRP, most researchers concentrate on using meta-heuristics for solving real-life problems. In this paper, heuristic methods based on Ant Colony Optimization and Simulated Annealing algorithms are developed and search strategies are investigated. Computational results are reported on randomly generated problems. These methods significantly improve in minimizing the total distances travelled by the vehicles.

Type 2 Fully Fuzzy Linear Programming

2021 ◽  
Vol 10 (4) ◽  
pp. 37-56
Author(s):  
Mohamed El Alaoui
Keyword(s):  
Linear Programming ◽  
Real Life ◽  
Inequality Constraints ◽  
Fuzzy Linear Programming ◽  
Fuzzy Membership Function ◽  
Programming Approach ◽  
Life Problems ◽  
Comparative Results ◽  
Interval Type

Since its inception, fuzzy linear programming (FLP) has proved to be a more powerful tool than classical linear programming to optimize real-life problems dealing with uncertainty. However, the proposed models are partially fuzzy; in other words, they suppose that only some aspects can be uncertain, while others have to be crisp. Furthermore, the few methods that deal with fully fuzzy problems use Type 1 fuzzy membership function, while Type 2 fuzzy logic captures the uncertainty in a more suitable way. This work presents a fully fuzzy linear programming approach in which all parameters are represented by unrestricted Interval Type 2 fuzzy numbers (IT2FN) and variables by positive IT2FN. The treated comparative results show that the proposed achieves a better optimized function while permitting consideration of both equality and inequality constraints.

scholarly journals A mathematical model for the route optimization of service vehicles

2017 ◽  
Vol 7 (1) ◽  
pp. 152-158
Author(s):  
İlker Küçükoğlu ◽  
Dilara Zümbülova ◽  
Koray Reyhan ◽  
Salih Görgülü ◽  
Nursel Öztürk
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Real Life ◽  
Route Planning ◽  
Transportation Cost ◽  
Route Optimization ◽  
Mixed Integer ◽  
Total Transportation Cost ◽  
The Mathematical Model ◽  
Service Vehicles

The route planning of service vehicles is an important issue for large-scale enterprises which have hundreds of employee. Especially for the flexible shift system which brings about uncertainty for the drivers, the route plans have to be formed daily by the managers. This study addresses the route optimization problem of an automotive company which aims to minimize total transportation cost of the service fleet and proposes a mixed integer mathematical model to solve problem. The objective of the mathematical model is to minimize fixed and transportation cost of the fleet by considering vehicle capacities and travelling time constraints. The mathematical model is tested on a randomly generated problem set which consist of different sized instances for homogeneous service fleet. The computational results obtained by the Gurobi solver show that the proposed mathematical model is capable to find route plans for the real-life service vehicles routing decisions that can minimize total transportation cost of the fleet. Keywords: Vehicle routing, service systems, mathematical modelling;

The Psychologist in the Medical School: An Example of Solving Real-Life Problems

1970 ◽  
Author(s):  
Matisyohu Weisenberg ◽  
Carl Eisdorfer ◽  
C. Richard Fletcher ◽  
Murray Wexler
Keyword(s):  
Medical School ◽  
Real Life ◽  
Life Problems

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

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