scholarly journals Stability of Solutions for Parametric Inverse Nonlinear Cost Transportation Problem

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2027
Author(s):  
Abd Allah A. Mousa ◽  
Yousria Abo-Elnaga
Keyword(s):  
Nonlinear Programming ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Optimal Solution ◽  
Solution Stability ◽  
Tuning Parameters ◽  
Input Parameters ◽  
Feasible Alternative ◽  
The Stability ◽  
The Cost

This paper investigates the solution for an inverse of a parametric nonlinear transportation problem, in which, for a certain values of the parameters, the cost of the unit transportation in the basic problem are adapted as little as possible so that the specific feasible alternative become an optimal solution. In addition, a solution stability set of these parameters was investigated to keep the new optimal solution (feasible one) is unchanged. The idea of this study based on using a tuning parameters λ∈Rm in the function of the objective and input parameters υ∈Rl in the set of constraint. The inverse parametric nonlinear cost transportation problem P(λ,υ), where the tuning parameters λ∈Rm in the objective function are tuned (adapted) as less as possible so that the specific feasible solution x∘ has been became the optimal ones for a certain values of υ∈Rl, then, a solution stability set of the parameters was investigated to keep the new optimal solution x∘ unchanged. The proposed method consists of three phases. Firstly, based on the optimality conditions, the parameter λ∈Rm are tuned as less as possible so that the initial feasible solution x∘ has been became new optimal solution. Secondly, using input parameters υ∈Rl resulting problem is reformulated in parametric form P(υ). Finally, based on the stability notions, the availability domain of the input parameters was detected to keep its optimal solution unchanged. Finally, to clarify the effectiveness of the proposed algorithm not only for the inverse transportation problems but also, for the nonlinear programming problems; numerical examples treating the inverse nonlinear programming problem and the inverse transportation problem of minimizing the nonlinear cost functions are presented.

scholarly journals PENYELESAIAN MODEL TRANSPORTASI MENGGUNAKAN METODE ASM

2020 ◽  
Vol 14 (1) ◽  
pp. 40
Author(s):  
Nurul Iftitah ◽  
Pardi Affandi ◽  
Akhmad Yusuf
Keyword(s):  
Transportation Problem ◽  
Feasible Solution ◽  
Direct Method ◽  
Optimal Solution ◽  
Transportation Model ◽  
Initial Feasible Solution ◽  
The Cost

(demand). the method that could be used for solving the transportation problem is to directly find the optimal solution. The direct method that used in this study id the ASM method for solving the balance transportation problem and revised ASM method for solving the unbalance transportation problem. This study aims to construct a transportation model using those methods and it solution. The method on this study is to identify the transportation model, construct the transportation model matrixes, construct an algorithm table using ASM method and to determine the optimal solution of the transportation problem. The obtained result from this study was the model ASM method could determine the optimum value without using initial feasible solution. On solving the unbalance transportation problem, there is an addition of dummy cell or column step. Then reducing the cost of cell and column and change the dummy cost with the biggest cost of reduced cell or column.

scholarly journals Goal programming approach for solving heptagonal fuzzy transportation problem under budgetry constraint

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Hamiden Abd El-Wahed Khalifa
Keyword(s):  
Goal Programming ◽  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Optimal Solution ◽  
Programming Approach ◽  
Solution Approach ◽  
Fuzzy Transportation Problem ◽  
The Stability ◽  
The Cost

Transportation problem (TP) is a special type of linear programming problem (LPP) where the objective is to minimize the cost of distributing a product from several sources (or origins) to some destinations. This paper addresses a transportation problem in which the costs, supplies, and demands are represented as heptagonal fuzzy numbers. After converting the problem into the corresponding crisp TP using the ranking method, a goal programming (GP) approach is applied for obtaining the optimal solution. The advantage of GP for the decision-maker is easy to explain and implement in real life transportation. The stability set of the first kind corresponding to the optimal solution is determined. A numerical example is given to highlight the solution approach.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Managing cost uncertainties in transportation and assignment problems

1998 ◽  
Vol 2 (1) ◽  
pp. 65-104 ◽  
Author(s):  
V. Adlakha ◽  
H. Arsham
Keyword(s):  
Time Lag ◽  
Real Life ◽  
Optimal Solution ◽  
Global Market ◽  
Solution Algorithm ◽  
Assignment Problems ◽  
The Stability ◽  
Order Assignment ◽  
Cost Parameters ◽  
The Cost

In a fast changing global market, a manager is concerned with cost uncertainties of the cost matrix in transportation problems (TP) and assignment problems (AP).A time lag between the development and application of the model could cause cost parameters to assume different values when an optimal assignment is implemented. The manager might wish to determine the responsiveness of the current optimal solution to such uncertainties. A desirable tool is to construct a perturbation set (PS) of cost coeffcients which ensures the stability of an optimal solution under such uncertainties.The widely-used methods of solving the TP and AP are the stepping-stone (SS) method and the Hungarian method, respectively. Both methods fail to provide direct information to construct the needed PS. An added difficulty is that these problems might be highly pivotal degenerate. Therefore, the sensitivity results obtained via the available linear programming (LP) software might be misleading.We propose a unified pivotal solution algorithm for both TP and AP. The algorithm is free of pivotal degeneracy, which may cause cycling, and does not require any extra variables such as slack, surplus, or artificial variables used in dual and primal simplex. The algorithm permits higher-order assignment problems and side-constraints. Computational results comparing the proposed algorithm to the closely-related pivotal solution algorithm, the simplex, via the widely-used pack-age Lindo, are provided. The proposed algorithm has the advantage of being computationally practical, being easy to understand, and providing useful information for managers. The results empower the manager to assess and monitor various types of cost uncertainties encountered in real-life situations. Some illustrative numerical examples are also presented.

A Study on Cooperative Continuous Static Games without Differentiability under Fuzzy Environment

2022 ◽  
Vol 11 (1) ◽  
pp. 0-0
Keyword(s):  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Solution Concept ◽  
Proper Understanding ◽  
Fuzzy Environment ◽  
The Stability ◽  
The Right ◽  
The Cost ◽  
Stability Sets ◽  
Fuzzy Parameters

In this study, a fuzzy cooperative continuous static game (PQFCCSG) with n players having fuzzy parameters in all of the cost functions and the right- hand-side of constraints is characterized. Their fuzzy parameters are represented by piecewise quadratic fuzzy numbers. The α-pareto optimal solution concept is specified. In addition, the stability sets of the first and second kind without differentiability are conceptualized and established. An illustrated numerical example is discussed for proper understanding and interpretation of the proposed concept.

Solving Solid Transportation Problems With Multi-Choice Cost and Stochastic Supply and Demand

2018 ◽  
pp. 137-170 ◽  
Author(s):  
Sankar Kumar Roy ◽  
Deshabrata Roy Mahapatra
Keyword(s):  
Stochastic Programming ◽  
Objective Function ◽  
Transportation Problem ◽  
Supply And Demand ◽  
Optimal Solution ◽  
Programming Approach ◽  
Solid Transportation Problem ◽  
New Approach ◽  
Non Linear Programming ◽  
The Cost

In this chapter, the authors propose a new approach to analyze the Solid Transportation Problem (STP). This new approach considers the multi-choice programming into the cost coefficients of objective function and stochastic programming, which is incorporated in three constraints, namely sources, destinations, and capacities constraints, followed by Cauchy's distribution for solid transportation problem. The multi-choice programming and stochastic programming are combined into a solid transportation problem, and this new problem is called Multi-Choice Stochastic Solid Transportation Problem (MCSSTP). The solution concepts behind the MCSSTP are based on a new transformation technique that will select an appropriate choice from a set of multi-choice, which optimize the objective function. The stochastic constraints of STP converts into deterministic constraints by stochastic programming approach. Finally, the authors construct a non-linear programming problem for MCSSTP, and by solving it, they derive an optimal solution of the specified problem. A realistic example on STP is considered to illustrate the methodology.

Generalized explicit guidance with optimal time-to-go and realistic final velocity

2019 ◽  
Vol 233 (13) ◽  
pp. 4926-4942
Author(s):  
Sabyasachi Mondal ◽  
Radhakant Padhi
Keyword(s):  
Optimal Solution ◽  
Optimal Time ◽  
Optimal Solutions ◽  
Final Velocity ◽  
Velocity Magnitude ◽  
Guidance Law ◽  
Optimal Guidance ◽  
Input Parameters ◽  
The Cost

This paper presents an approach to compute the optimal time-to-go and final velocity magnitude in the Generalized Explicit (GENEX) guidance. Time-to-go and final velocity magnitude are two critical input parameters in GENEX guidance implementation. Optimal time-to-go selects that optimal solution which yields less cost compared to the costs yielded by other optimal solutions. In addition to it, the input of realistic final velocity lowers the cost further. These developments relax the existing limitations of GENEX, thereby making this optimal guidance law more optimal, effective and generic.

scholarly journals Solar Simulation Model to Find Optimal Solution for Domestic Load

2021 ◽  
Vol 9 (VII) ◽  
pp. 2643-2646
Author(s):  
Mujeeb Jeelani Magray
Keyword(s):  
Feasible Solution ◽  
Optimal Solution ◽  
Power Production ◽  
Solar Pv ◽  
Environment Friendly ◽  
Power Outage ◽  
The World ◽  
Cost Competitiveness ◽  
The Cost

Looking at the energy sector of India, it is the 3rd largest producer in the world and holds the largest grid in the world. Despite the presence of largest grid, still frequent power outage, delivery of low quality of power and unreliability of supply persistent in some areas. This unreliable power supply creates hindrance in the overall development of the region. On the other hand solar power is most widely used source of renewable energy, can be able to provide feasible solution. By installation of solar PV array in the premises of the load center the reliability will be increased. The power production from the PV is also cost competitive and environment friendly. As solar PV power is intermittent in nature, the most old and mature storage technology ,i.e. battery can be integrated to mitigate this intermittency nature. The present study examines the feasibility and optimizes the size of such system, while the cost competitiveness is kept at the center.

scholarly journals Fundamentals of Transportation Problem

2021 ◽  
Vol 10 (5) ◽  
pp. 90-103
Author(s):  
Bhabani Mallia ◽  
Manjula Das ◽  
C. Das
Keyword(s):  
Linear Programming ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Optimal Solution ◽  
Optimal Solutions ◽  
Basic Feasible Solution ◽  
Distribution Method

Transportation Problem is a linear programming problem. Like LPP, transportation problem has basic feasible solution (BFS) and then from it we obtain the optimal solution. Among these BFS the optimal solution is developed by constructing dual of the TP. By using complimentary slackness conditions the optimal solutions is obtained by the same iterative principle. The method is known as MODI (Modified Distribution) method. In this paper we have discussed all the aspect of transportation problem.

scholarly journals Fuzzy Hungarian Approach for Transportation Model

2013 ◽  
pp. 189-192
Author(s):  
Arun Patil ◽  
S. B. Chandgude
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Real Life ◽  
Optimal Solution ◽  
Transportation Model ◽  
Trapezoidal Fuzzy Numbers ◽  
Fuzzy Optimal Solution ◽  
Transportation Models ◽  
Fuzzy Transportation Problem ◽  
The Cost

In this paper, a method is proposed to find the fuzzy optimal solution of fuzzy transportation model by representing all the parameters as trapezoidal fuzzy numbers. To illustrate the proposed method a fuzzy transportation problem is solved by using the proposed method and the results are obtained. The proposed method is easy to understand, and to apply for finding the fuzzy optimal solution of fuzzy transportation models in real life situations. However, we propose the method of fuzzy modified distribution for finding out the optimal solution for minimizing the cost of total fuzzy transportation. The advantages of the proposed method are also discussed.

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