Incessant Allocation Method for Solving Transportation Problems

Ahmed, Mollah Mesbahuddin; Khan, Aminur Rahman; Ahmed, Faruque; Uddin, Md. Sharif

doi:10.4236/ajor.2016.63024

Cited by 20 publications

(13 citation statements)

References 7 publications

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“…is provided in Appendix 1. [4]. The comparative results obtained in Table 1 are also depicted using bar graphs and the results are given in Figure 1.…”

Section: A Comparison Of the Methodsmentioning

confidence: 99%

An Effective Alternative New Approach in Solving Transportation Problems

Ekanayake¹,

Perera²,

Daundasekara³

et al. 2021

AJECE

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The Transportation problem is one of the most colorful and demanding problems in the history of Operations Research. Many researchers have paid attention to solve the problem using different approaches. In certain approaches focused on finding an initial basic feasible solution and the other to find the optimal solution. It can be noticed that these methods have advantages and disadvantages. Out of all the methods that can be found in the literature, Northwest, Least Cost and Vogel's Approximation methods are the most prominent and renowned methods in finding an initial basic feasible solution. Also, the Modified Distribution (MODI) Method and Stepping Stone Method are the most acceptable methods in finding the optimal solution to the transportation problem. In this research paper, we propose an alternative method that finds the optimal or nearly optimal solution to the transportation problem. This method which is based on an iterative algorithm can be applied to balance as well as unbalanced transportation problems. It is also to be noticed that this method requires a minimum number of iterations to reach the optimality as compared to the other existing methods. Also, we have developed a new method of finding an optimal solution for both balanced and unbalanced transportation problems.

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“…is provided in Appendix 1. [4]. The comparative results obtained in Table 1 are also depicted using bar graphs and the results are given in Figure 1.…”

Section: A Comparison Of the Methodsmentioning

confidence: 99%

An Effective Alternative New Approach in Solving Transportation Problems

Ekanayake¹,

Perera²,

Daundasekara³

et al. 2021

AJECE

View full text Add to dashboard Cite

show abstract

“…Operations research provides different methods that can be applied to solve such assignment problems. Integer Linear Programming (ILP), the Hungarian Method (HM) or Vogel's Approximation Method (VAM) are frequently used in related literature (Paul 2018;Dinagar and Keerthivasan 2018;Nahar et al 2018;Ahmed et al 2016;Korukoglu and Ballı 2011;Balakrishnan 1990). The underlying paper proposes an adapted version of VAM which reaches better solutions for non-quadratic matrices, namely Vogel's Approximation Method for non-quadratic Matrices (VAM-nq).…”

Section: Solving Non-quadratic Matrices In Assignment Problems With An Improved Version Of Vogel's Approximation Methodsmentioning

confidence: 99%

ECMS 2019 Proceedings edited by Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco

2019

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The 33rd edition of the ECMS conference, a widely consolidated interdisciplinary forum for simulation and modeling researchers and practitioners that keeps its reference position year after year, brings with it two novelties: a new name and a new form of publication. In fact, to better catch in the name the actual situation of participants, the European Council for Modelling and Simulation decided to rename the event as "ECMS International Conference on Modelling and Simulation". This year, we also start a new book series of annual volumes, namely "Communications of the ECMS", which replaces the name "Proceedings" in order to acknowledge the recognition and reputation of the scientific community of simulation. This year the chosen conference venue is in Caserta, Italy. The Università degli Studi della Campania "Luigi Vanvitelli", previously known as Seconda Università degli Studi di Napoli, a state-owned university founded in 1990 with the explicit mission of meeting the cultural demand of the population living in the northern part of Campania. Caserta, famous for its wonderful royal palace, whose facilities will host the conference, is a city with a long history, already inhabited in the 5th century BC. It flourished in the middle age and then in the XVI-XVII century AD, surrounded by a geographical area rich of historical relevance that was under Roman influence.The university is characterized by its diffusion over the territory of the province of Caserta, having its 16 departments located in Caserta, Aversa and Santa Maria Capua Vetere, and Napoli, in which its roots can be found: the most of the departments are located in historical landmarks, that have been saved and recovered by specific agreements and funding. More than 25000 students from Italy and abroad study at Vanvitelli University enrolled in bachelor, master and PhD. curricula, taught as well in Italian as in English, and covering different aspects of mathematics, physics, data analytics, engineering, law, economics, political sciences, medicine, nursery, biotechnology, pharmacy, environmental sciences, cultural heritage, literature, psychology, tourism, design and architecture.We are honored to offer, besides the scientific program of the conference, consisting in more than 65 high quality accepted papers, a rich and various series of social events, as usual for the spirit of this conference.

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“…The MACOA is validated using a numerical example. Detailed computation of this example using the proposed method (MACOA) is provided in Appendix F. The flow chart representation of the above MACOA is also provided below: Table 1 is provided in Appendix A [31]. The comparative results obtained in Table 1 are also depicted using bar graphs and the results are given in Fig.…”

Section: Modified Ant Colony Optimization Algorithm (Macoa)mentioning

confidence: 99%

A Modified Ant Colony Optimization Algorithm for Solving a Transportation Problem

Ekanayake

Perera

Daundasekara

et al. 2020

JAMCS

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Transportation of products from sources to destinations with minimal total cost plays a key role in logistics and supply chain management. The transportation problem (TP) is an extraordinary sort of Linear Programming problem where the objective is to minimize the total cost of disseminating resources from several various sources to several destinations. Initial feasible solution (IFS) acts as a foundation of an optimal cost solution technique to any TP. Better is the IFS lesser is the number of iterations to reach the final optimal solution. This paper presents a meta-heuristic algorithm, modified ant colony optimization algorithm (MACOA) to attain an IFS to a Transportation Problem. The proposed algorithm is straightforward, simple to execute, and gives us closeness optimal solutions in a finite number of iterations. The efficiency of this algorithm is likewise been advocated by solving validity and applicability examples An extensive numerical study is carried out to see the potential significance of our modified ant colony optimization algorithm (MACOA). The comparative assessment shows that both the MACOA and the existing JHM are efficient as compared to the studied approaches of this paper in terms of the quality of the solution. However, in practice, when researchers and practitioners deal with large-sized transportation problems, we urge them to use our proposed MACOA due to the time-consuming computation of JHM. Therefore this finding is important in saving time and resources for minimization of transportation costs and optimizing transportation processes which could help significantly to improve the organization’s position in the market.

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Incessant Allocation Method for Solving Transportation Problems

Cited by 20 publications

References 7 publications

An Effective Alternative New Approach in Solving Transportation Problems

An Effective Alternative New Approach in Solving Transportation Problems

ECMS 2019 Proceedings edited by Mauro Iacono, Francesco Palmieri, Marco Gribaudo, Massimo Ficco

A Modified Ant Colony Optimization Algorithm for Solving a Transportation Problem

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