scholarly journals Modified Approach for Optimization of Real Life Transportation Problem in Neutrosophic Environment

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Akanksha Singh ◽  
Amit Kumar ◽  
S. S. Appadoo
Keyword(s):  
Transportation Problem ◽  
Cost Minimization ◽  
Real Life ◽  
Exact Results ◽  
Transportation Problems ◽  
Incorrect Assumption ◽  
Time Minimization

To the best of our knowledge, there is only one approach for solving neutrosophic cost minimization transportation problems. Since neutrosophic transportation problems are a new area of research, other researchers may be attracted to extend this approach for solving other types of neutrosophic transportation problems like neutrosophic solid transportation problems, neutrosophic time minimization transportation problems, neutrosophic transshipment problems, and so on. However, after a deep study of the existing approach, it is noticed that a mathematical incorrect assumption has been used in these existing approaches; therefore there is a need to modify these existing approaches. Keeping the same in mind, in this paper, the existing approach is modified. Furthermore, the exact results of some existing transportation problems are obtained by the modified approach.

Methods for Solving Fully Fuzzy Transportation Problems Based on Classical Transportation Methods

2013 ◽  
pp. 328-347 ◽  
Author(s):  
Amit Kumar ◽  
Amarpreet Kaur
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
Programming Formulation ◽  
Transportation Problems ◽  
Fuzzy Optimal Solution ◽  
Linear Programming Formulation ◽  
Fuzzy Transportation Problem

There are several methods, in literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems by representing all the parameters as trapezoidal fuzzy numbers. The advantages of the proposed methods over existing methods are also discussed. To illustrate the proposed methods a fuzzy transportation problem (FTP) is solved by using the proposed methods and the obtained results are discussed. The proposed methods are easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

scholarly journals A review on fuzzy and stochastic extensions of the multi index transportation problem

2017 ◽  
Vol 27 (1) ◽  
pp. 3-29 ◽  
Author(s):  
Sungeeta Singh ◽  
Renu Tuli ◽  
Deepali Sarode
Keyword(s):  
Transportation Problem ◽  
Real Life ◽  
Review Article ◽  
Fixed Charge ◽  
Fixed Cost ◽  
Multi Index ◽  
Transportation Problems ◽  
Single Criterion ◽  
Fixed Charge Transportation Problem

The classical transportation problem (having source and destination as indices) deals with the objective of minimizing a single criterion, i.e. cost of transporting a commodity. Additional indices such as commodities and modes of transport led to the Multi Index transportation problem. An additional fixed cost, independent of the units transported, led to the Multi Index Fixed Charge transportation problem. Criteria other than cost (such as time, profit etc.) led to the Multi Index Bi-criteria transportation problem. The application of fuzzy and stochastic concept in the above transportation problems would enable researchers to not only introduce real life uncertainties but also obtain solutions of these transportation problems. The review article presents an organized study of the Multi Index transportation problem and its fuzzy and stochastic extensions till today, and aims to help researchers working with complex transportation problems.

scholarly journals A New Approach to Solve Mixed Constraint Transportation Problem Under Fuzzy Environment

2017 ◽  
Vol 16 (4) ◽  
pp. 6895-6902
Author(s):  
Nidhi Joshi ◽  
Surjeet Singh Chauhan (Gonder) ◽  
Raghu Raja
Keyword(s):  
Transportation Problem ◽  
Real Life ◽  
Optimal Solution ◽  
Optimal Solutions ◽  
New Approach ◽  
Transportation Problems ◽  
Mixed Constraints ◽  
Fuzzy Environment ◽  
Mixed Constraint ◽  
Fuzzy Transportation Problem

The present paper attempts to obtain the optimal solution for the fuzzy transportation problem with mixed constraints. In this paper, authors have proposed a new innovative approach for obtaining the optimal solution of mixed constraint fuzzy transportation problem. The method is illustrated using a numerical example and the logical steps are highlighted using a simple flowchart. As maximum transportation problems in real life have mixed constraints and these problems cannot be truly solved using general methods, so the proposed method can be applied for solving such mixed constraint fuzzy transportation problems to obtain the best optimal solutions.

scholarly journals A Simple and Efficient Algorithm for Solving Type-1 Intuitionistic Fuzzy Solid Transportation Problems

2018 ◽  
Vol 9 (3) ◽  
pp. 90-122 ◽  
Author(s):  
P. Senthil Kumar
Keyword(s):  
Transportation Problem ◽  
Feasible Solution ◽  
Real Life ◽  
Optimal Solution ◽  
Intuitionistic Fuzzy Number ◽  
Basic Feasible Solution ◽  
Transportation Problems ◽  
Intuitionistic Fuzzy ◽  
Triangular Intuitionistic Fuzzy Number

This article describes how in solving real-life solid transportation problems (STPs) we often face the state of uncertainty as well as hesitation due to various uncontrollable factors. To deal with uncertainty and hesitation, many authors have suggested the intuitionistic fuzzy (IF) representation for the data. In this article, the author tried to categorise the STP under uncertain environment. He formulates the intuitionistic fuzzy solid transportation problem (IFSTP) and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The STP has uncertainty and hesitation in supply, demand, capacity of different modes of transport celled conveyance and when it has crisp cost it is known as IFSTP of type-1. From this concept, the generalized mathematical model for type-1 IFSTP is explained. To find out the optimal solution to type-1 IFSTPs, a single stage method called intuitionistic fuzzy min-zero min-cost method is presented. A real-life numerical example is presented to clarify the idea of the proposed method. Moreover, results and discussions, advantages of the proposed method, and future works are presented. The main advantage of the proposed method is that the optimal solution of type-1 IFSTP is obtained without using the basic feasible solution and the method of testing optimality.

Methods for Solving Fully Fuzzy Transportation Problems Based on Classical Transportation Methods

2011 ◽  
Vol 2 (4) ◽  
pp. 52-71 ◽  
Author(s):  
Amit Kumar ◽  
Amarpreet Kaur
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Optimal Solution ◽  
Fuzzy Linear Programming ◽  
Transportation Problems ◽  
New Methods ◽  
Fuzzy Optimal Solution ◽  
Linear Programming Formulation ◽  
Fuzzy Transportation Problem

There are several methods, in literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems by representing all the parameters as trapezoidal fuzzy numbers. The advantages of the proposed methods over existing methods are also discussed. To illustrate the proposed methods a fuzzy transportation problem (FTP) is solved by using the proposed methods and the obtained results are discussed. The proposed methods are easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

Cost Minimization of Sensor Placement and Routing in Wireless Sensor Networks

2020 ◽  
pp. 1286-1301
Author(s):  
Tata Jagannadha Swamy ◽  
Garimella Rama Murthy
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cost Minimization ◽  
Real Life ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Technological Advances ◽  
Strongly Connected ◽  
Placement And Routing

Wireless Sensor Nodes (WSNs) are small in size and have limited energy resources. Recent technological advances have facilitated widespread use of wireless sensor networks in many real world applications. In real life situations WSN has to cover an area or monitor a number of nodes on a plane. Sensor node's coverage range is proportional to their cost, as high cost sensor nodes have higher coverage ranges. The main goal of this paper is to minimize the node placement cost with the help of uniform and non-uniform 2D grid planes. Authors propose a new algorithm for data transformation between strongly connected sensor nodes, based on graph theory.

scholarly journals PSK Method for Solving Intuitionistic Fuzzy Solid Transportation Problems

2018 ◽  
Vol 7 (4) ◽  
pp. 62-99 ◽  
Author(s):  
P.Senthil Kumar
Keyword(s):  
Real Life ◽  
Optimal Solution ◽  
Transportation Problems ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Optimal Solution ◽  
Fuzzy Representation ◽  
Objective Value

This article proposes a method for solving intuitionistic fuzzy solid transportation problems (IFSTPs) in which only the transportation costs are represented in terms of intuitionistic fuzzy numbers (IFNs). The remaining parameters, namely: supply, demand and conveyance capacity, are all considered into crisp numbers. This type of STP is called a type-2 IFSTP. When solving the real life solid transportation problems (STPs) those tend to face the uncertainty state as well as hesitation due to many uncontrollable factors. To deal with uncertainty and hesitation many authors have suggested the intuitionistic fuzzy representation for the data. In this article, the author tried to categorise the STPs under the uncertain environment. He formulates the intuitionistic fuzzy STPs and utilizes the triangular intuitionistic fuzzy number (TIFN) to deal with uncertainty and hesitation. The PSK (P.Senthil Kumar) method for finding an intuitionistic fuzzy optimal solution for fully intuitionistic fuzzy transportation problem (FIFTP) is extended to solve the type-2 IFSTP and the optimal objective value of type-2 IFSTP is obtained in terms of TIFN. The main advantage of this method is that the optimal solution of type-2 IFSTP is obtained without using the basic feasible solution and the method of testing optimality. Moreover, the proposed method is computationally very simple and easy to understand. A case study is presented to illustrate the procedure of the proposed method.

scholarly journals Optimized Procedure to Schedule Physicians in an Intensive Care Unit: A Case Study

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1976
Author(s):  
Lotfi Hidri ◽  
Achraf Gazdar ◽  
Mohammed M. Mabkhot
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Cost Minimization ◽  
Optimal Schedule ◽  
Real Life ◽  
Real Data ◽  
Experimental Tests ◽  
Operating Costs ◽  
Healthcare Personnel ◽  
Total Cost

Hospitals are facing an important financial pressure due to the increasing of the operating costs. Indeed, the growth for the hospitals’ services demand causes a rising in the number of required qualified personnel. Enlarging the personnel number increases dramatically the fixed total cost. Based on some studies, 50% of operating costs in US hospitals are allocated to healthcare personnel. Therefore, reducing these types of costs without damaging the service quality becomes a priority and an obligation. In this context, several studies focused on minimizing the total cost by producing optimal or near optimal schedules for nurses and physicians. In this paper, a real-life physicians scheduling problem with cost minimization is addressed. This problem is encountered in an Intensive Care Unit (ICU) where the current schedule is manually produced. The manual schedule is generating a highly unbalanced load within physicians in addition to a high cost overtime. The manual schedule preparation is a time consuming procedure. The main objective of this work is to propose a procedure that systematically produces an optimal schedule. This optimal schedule minimizes the total overtime within a short time and should satisfies the faced constraints. The studied problem is mathematically formulated as an integer linear program. The constraints are real, hard, and some of them are non-classical ones (compared to the existing literature). The obtained mathematical model is solved using a state-of-the-art software. Experimental tests on real data have shown the performance of the proposed procedure. Indeed, the new optimal schedules reduce the total overtime by up to 69%. In addition, a more balanced workload for physicians is obtained and several physician preferences are now satisfied.

Three-phase time minimization transportation problem

2020 ◽  
pp. 1-13
Author(s):  
Ekta Jain ◽  
Kalpana Dahiya ◽  
Vanita Verma
Keyword(s):  
Transportation Problem ◽  
Phase Time ◽  
Three Phase ◽  
Time Minimization
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