Papers by Ramasamy Panneerselvam
The productivity of an organization is very much affected by non-value adding activity like logis... more The productivity of an organization is very much affected by non-value adding activity like logistics , which moves the resources from suppliers to factory, raw materials/semi-finished items within the factory and finished goods from factory to customers via a designated distribution channel called as forward logistics. In some cases, parts of the products such as automobiles, computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery strategy through reverse logistics network which is integrated in a sustainable closed loop supply chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics network. This paper gives a comprehensive review of literature of the design of networks for the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions of the researchers are classified into nine categories based on the methods used to design the logistics network.
Journal of Service Science and Management, 2015
Intelligent Information Management, 2015
ABSTRACT
This paper presents four different hybrid genetic algorithms for network design problem ... more ABSTRACT
This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.
KEYWORDS
Closed Loop Supply Chain, Genetic Algorithms, HGA, Meta-Heuristics, MINLP, Model, Network Design, Optimization
This paper discusses a heuristic to minimize the makespan in uniform parallel machines scheduling... more This paper discusses a heuristic to minimize the makespan in uniform parallel machines scheduling problem. Normally, researchers assume the parallel machines with the same speed. But, in reality, under single machine scheduling, the jobs may have proportional processing times on the parallel machines. Such parallel machines are called uniform parallel machines. In the first phase of this paper, a mathematical model is developed to obtain the optimal makespan of the schedule for a given set of single operation jobs on these uniform parallel machines. Then, an attempt is made to develop a heuristic to minimize the makespan of the schedule for the given set of jobs on the uniform parallel machines of the single machine scheduling problem. At the end, the solutions of the heuristic are compared with that of a mathematical model, which gives optimal solutions, for randomly generated problems. It is found that the heuristic solutions do not significantly differ from the optimal solutions of the problems.
Intelligent Information Management, 2010
This paper discusses design and comparison of Simulated Annealing Algorithm and Greedy Randomized... more This paper discusses design and comparison of Simulated Annealing Algorithm and Greedy Randomized Adaptive Search Procedure (GRASP) to minimize the makespan in scheduling n single operation independent jobs on m unrelated parallel machines. This problem of minimizing the makespan in single machine scheduling problem with uniform parallel machines is NP hard. Hence, heuristic development for such problem is highly inevitable. In this paper, two different Meta-heuristics to minimize the makespan of the assumed problem are designed and they are compared in terms of their solutions. In the first phase, the simulated annealing algorithm is presented and then GRASP (Greedy Randomized Adaptive Search procedure) is presented to minimize the makespan in the single machine scheduling problem with unrelated parallel machines. It is found that the simulated annealing algorithm performs better than GRASP.
Intelligent Information Management, 2015
This paper considers machine-component cell formation problem of cellular manufacturing system. S... more This paper considers machine-component cell formation problem of cellular manufacturing system. Since this problem comes under combinatorial category, development of a meta-heuristic is a must. In this paper, a hybrid genetic algorithm is presented. Normally, in genetic algorithm, the initial population is generated by random assignment of genes in each of the chromosomes. In this paper, the initial population is created using ideal seed heuristic. The proposed algorithm is compared with four other algorithms using 28 problems from literature. Through a completed factorial experiment, it is observed that the proposed algorithm outperforms the other algorithms in terms of grouping efficiency as well as grouping efficacy.
The integration of entire supply and value chain into a closed loop network is gaining more impor... more The integration of entire supply and value chain into a closed loop network is gaining more importance
in recent times in order to ensure a business to be economically and environmentally
sustainable with the changing trends in business and social environments, growing environmental
consciousness in the society and government legislations to protect the environment as well as the
business. In this context, this paper considers a multi-echelon closed loop supply chain network
design with forward and reverse logistics components. An attempt has been made to develop a
mixed integer non-linear programming model for this problem with different costs so that the
sum of the total cost is minimized subject to different constraints pertaining to capacities of the
entities of the system, demands of first customers and second customers. A generalized model is
presented and then its application is illustrated using an example problem by solving the model
using LINGO14. This model forms as a tool to compare future meta-heuristics to check the closeness
of their solutions with corresponding optimal solutions.
Intelligent Information Management, 2012
In this paper, we have conducted a literature review on the recent developments and publications ... more In this paper, we have conducted a literature review on the recent developments and publications involving the vehicle routing problem and its variants, namely vehicle routing problem with time windows (VRPTW) and the capacitated vehicle routing problem (CVRP) and also their variants. The VRP is classified as an NP-hard problem. Hence, the use of exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. The vehicle routing problem comes under combinatorial problem. Hence, to get solutions in determining routes which are realistic and very close to the optimal solution, we use heuristics and meta-heuristics. In this paper we discuss the various exact methods and the heuristics and meta-heuristics used to solve the VRP and its variants.
Intelligent Information Management, 2010
This paper discusses an efficient heuristic to minimize the makespan of scheduling n independent ... more This paper discusses an efficient heuristic to minimize the makespan of scheduling n independent jobs on m unrelated parallel machines. The problem of scheduling the jobs on the unrelated parallel machines is combinatorial in nature. Hence, the heuristic approach is inevitable for quicker solution. In this paper, a simple and efficient heuristic is designed to minimize the makespan of scheduling n independent jobs on m unrelated parallel machines. A mathematical model is also presented for this problem. A factorial experiment is used to compare the results of the proposed heuristic with that of a mathematical model by taking "Method" (Heuristic and Model) as the first factor and "Problem Size" (No. of machines X No. of Jobs: 2X5, 2X6, ……, 2X9, 3X5, 3X6, ……, 3X9, ……., 5X5, 5X6, …5X9) as the second factor. It is found that there is no significant difference between the results of the proposed heuristic and that of the mathematical model. Further, the mean percent error of the results obtained by the heuristic from the optimal results obtained by the model is 2.336 %. The heuristic gives optimal solution for 76.67 % of the problems.
The productivity of an organization is very much affected by non-value adding activity like logis... more The productivity of an organization is very much affected by non-value adding activity like logistics,
which moves the resources from suppliers to factory, raw materials/semi-finished items
within the factory and finished goods from factory to customers via a designated distribution
channel called as forward logistics. In some cases, parts of the products such as automobiles,
computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and
empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery
strategy through reverse logistics network which is integrated in a sustainable closed loop supply
chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics
network. This paper gives a comprehensive review of literature of the design of networks for
the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions
of the researchers are classified into nine categories based on the methods used to design
the logistics network.
International Journal of Services, Economics and Management, 2010
... CN Vijeyamurthy is an Assistant Professor in the Department of Management, Pallavan College o... more ... CN Vijeyamurthy is an Assistant Professor in the Department of Management, Pallavan College of Engineering, Kancheepuram, India. ... Panneerselvam and Balasubramanian (1985) have developed a set covering heuristic to determine the economical number of manufacturing ...
Intelligent Information Management, 2015
This paper discusses review of literature of open shop scheduling problems. First, the problem is... more This paper discusses review of literature of open shop scheduling problems. First, the problem is classified as per different measures of performance, viz., minimization of makespan, minimization of sum of completion times of jobs, minimization of sum of weighted completion times of all jobs, minimization of total tardiness of all jobs, minimization of sum of weighted tardiness of all jobs, minimization of weighted sum of tardy jobs, and miscellaneous measures of the open shop scheduling problem. In each category, the literature is further classified based on approaches used and then the contributions of researchers in the respective categories are presented. Directions for future research are discussed in the end. 1 2 , n J J J and a set M which consists of m machines { } 1 2
This research paper deals with the implementation of suitable meta-heuristic for the closed loop ... more This research paper deals with the implementation of suitable meta-heuristic for the closed loop supply chain network design problem of a fashion product industry. First, the paper presents a comprehensive literature review on the applications of reverse and closed loop supply chain network design problems in Fashion Footwear Industry. The research work employs the case study approach to implement the model and algorithm. Closed loop supply chain network design problem of a Fashion Footwear Industry in South India is studied and considered for the purpose. Then it deals with the application of mathematical model and a suitable hybrid genetic algorithm (HGA) developed for the CLSC network design problem of the Industry this research. The MINLP model and suitable HGA developed are implemented in the industrial case as per the reverse supply chain process conditions and model adopted in the respective closed loop supply chain and the results are presented.
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Papers by Ramasamy Panneerselvam
This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.
KEYWORDS
Closed Loop Supply Chain, Genetic Algorithms, HGA, Meta-Heuristics, MINLP, Model, Network Design, Optimization
in recent times in order to ensure a business to be economically and environmentally
sustainable with the changing trends in business and social environments, growing environmental
consciousness in the society and government legislations to protect the environment as well as the
business. In this context, this paper considers a multi-echelon closed loop supply chain network
design with forward and reverse logistics components. An attempt has been made to develop a
mixed integer non-linear programming model for this problem with different costs so that the
sum of the total cost is minimized subject to different constraints pertaining to capacities of the
entities of the system, demands of first customers and second customers. A generalized model is
presented and then its application is illustrated using an example problem by solving the model
using LINGO14. This model forms as a tool to compare future meta-heuristics to check the closeness
of their solutions with corresponding optimal solutions.
which moves the resources from suppliers to factory, raw materials/semi-finished items
within the factory and finished goods from factory to customers via a designated distribution
channel called as forward logistics. In some cases, parts of the products such as automobiles,
computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and
empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery
strategy through reverse logistics network which is integrated in a sustainable closed loop supply
chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics
network. This paper gives a comprehensive review of literature of the design of networks for
the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions
of the researchers are classified into nine categories based on the methods used to design
the logistics network.
This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.
KEYWORDS
Closed Loop Supply Chain, Genetic Algorithms, HGA, Meta-Heuristics, MINLP, Model, Network Design, Optimization
in recent times in order to ensure a business to be economically and environmentally
sustainable with the changing trends in business and social environments, growing environmental
consciousness in the society and government legislations to protect the environment as well as the
business. In this context, this paper considers a multi-echelon closed loop supply chain network
design with forward and reverse logistics components. An attempt has been made to develop a
mixed integer non-linear programming model for this problem with different costs so that the
sum of the total cost is minimized subject to different constraints pertaining to capacities of the
entities of the system, demands of first customers and second customers. A generalized model is
presented and then its application is illustrated using an example problem by solving the model
using LINGO14. This model forms as a tool to compare future meta-heuristics to check the closeness
of their solutions with corresponding optimal solutions.
which moves the resources from suppliers to factory, raw materials/semi-finished items
within the factory and finished goods from factory to customers via a designated distribution
channel called as forward logistics. In some cases, parts of the products such as automobiles,
computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and
empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery
strategy through reverse logistics network which is integrated in a sustainable closed loop supply
chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics
network. This paper gives a comprehensive review of literature of the design of networks for
the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions
of the researchers are classified into nine categories based on the methods used to design
the logistics network.