Dr. Susmita Bandyopadhyay | Burdwan University (original) (raw)

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Papers by Dr. Susmita Bandyopadhyay

Production and Operations Analysis, 2019

This paper applies a routing strategy based on Tarantula Mating Behavior as proposed by the autho... more This paper applies a routing strategy based on Tarantula Mating Behavior as proposed by the authors, Bandyopadhyay and Bhattacharya [1], on a manufacturing network. The particular behavior which is of interest is that the female Tarantula spider sometimes eats the male Tarantula just after mating for satisfying immediate need for food or for genetic purpose. This interesting behavior has been simulated with the help of a hierarchical multi-agent based framework where the master agent at the top of the hierarchy takes the final decision with the help of PROMETHEE multi-criteria decision analysis technique, based on the data for various criteria as delivered by the worker agents at the leaf level of the hierarchy. Fuzzy orientation has been added to the measurement for one of the criteria and in the calculation of PROMETHEE decision analysis technique. The strategy has been applied successfully on a manufacturing network.

Production and Operations Analysis, 2019

Production and Operations Analysis, 2019

A very interesting behavior as observed by author for Tarantula spider is that the female spider ... more A very interesting behavior as observed by author for Tarantula spider is that the female spider sometimes eats the male spider just after their mating in order to immediate need for food. This strange behavior has been used to propose a multi-agent and multi-criteria fuzzy routing strategy to be applied in manufacturing situations. A hierarchical structure of agents has been considered where the worker agents at the leaf level calculate shortest paths, congestion in a path, number of intermediate nodes and identify deadlock condition in the network. A master agent at the top of the hierarchy controls them. Fuzzy theory concepts have been used in case of shortest path calculation and in the calculations for PROMETHEE multi-criteria decision analysis. A network instance has used in order to implement the strategy as proposed in this research study.

2017 Second International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2017

This paper proposes fuzzy probabilistic TOPSIS outranking multi-criteria decision making techniqu... more This paper proposes fuzzy probabilistic TOPSIS outranking multi-criteria decision making technique and applies the proposed technique to a real-life multi-criteria case study. In many situations, selection of particular alternatives based on certain criteria found out to be uncertain. In such conflicting situations, probabilistic treatment for the alternatives is required. Since the determination of values of such probabilities is difficult and unrealistic as well, thus this paper proposes fuzzy probability values for the alternatives. The fuzzy probabilistic TOPSIS outranking technique is applied for the purpose. Numerical example through a case shows the applicability of the proposed technique.

Intelligent Information Management, 2012

Asian Journal of Research in Business Economics and Management, 2015

Stage shop scheduling is an emergent area in the field of scheduling. This paper has proposed a b... more Stage shop scheduling is an emergent area in the field of scheduling. This paper has proposed a bi-objective stage shop scheduling problem with total completion time and total tardiness of jobs, as objectives. In order to solve the proposed formulated problem, modified NSGA-II (Nondominated Sorting Genetic Algorithm – II) and modified MOPSO (Multi-Objective Particle Swarm Optimization) have been proposed. A mutation algorithm for NSGA-II and a velocity updation algorithm based on circular motion of alleles (for NSGA-II) and circular motion of particles (for MOPSO) have also been introduced and have been embedded in the proposed algorithms. The experimental results show that NSGA-II performs better than MOPSO in some aspects, whereas MOPSO performs better than NSGA-II in some other aspects.

This chapter presents an overview of various nature-based algorithms to solve multi-objective pro... more This chapter presents an overview of various nature-based algorithms to solve multi-objective problems with the particular emphasis on Multi-Objective Evolutionary Algorithms based on Genetic Algorithm. Some of the significant hybridization and the modification of the benchmark algorithms have also been discussed as well. The complexity issues have been outlined and various test problems to show the effectiveness of such algorithms have also been summarized. At the end, a brief discussion on the software packages used to model these type of algorithms are presented.

Advances in Intelligent Systems and Computing, 2013

Journal of Manufacturing Systems, 2014

Abstract In this paper, we propose the modification of an existing Multi-Objective Evolutionary A... more Abstract In this paper, we propose the modification of an existing Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm has been applied on a tri-objective problem for a two echelon serial supply chain. The objectives considered are: (1) minimization of the total cost of a two-echelon serial supply chain and (2) minimization of the variance of order quantity and (3) minimization of the total inventory. The variance of order quantity is an important factor to consider since the variance of order quantity is used to measure the bullwhip effect which is one of the performance measures of a supply chain. The supply chain under consideration is assumed to consist of buyers and supplier. The production process at the supplier is an imperfect production process and thus produces defective items. A percentage of defective items are sold at a secondary market and the remaining defective items are repaired. We have introduced a mutation algorithm which has been embedded in the proposed algorithm. Since the proposed mutation algorithm is performed over the entire population, thus the mutation algorithm has caused the modification of the parts of the original NSGA-II. The results of the modified algorithm have been compared with those of the original NSGA-II and SPEA2 (Strength Pareto Evolutionary Algorithm 2) evolutionary algorithms for varying values of probability of crossover. The experimental results show that the proposed algorithm performs significantly better than the original NSGA-II and SPEA2.

Journal of Intelligent Manufacturing, 2011

This paper minimizes the value of total cost and bullwhip effect in a supply chain. The objective... more This paper minimizes the value of total cost and bullwhip effect in a supply chain. The objectives have been achieved through developing a new multi-objective formulation for minimizing the total cost and minimizing the bullwhip effect of a two-echelon serial supply chain. A new crossover algorithm for a fuzzy variable and a new mutation algorithm have also been proposed while applying Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to the proposed problem. The formulated problem has been simulated by Matlab software and the results of the modified NSGA-II have been compared with those of original NSGA-II. It is found from the results that the modified NSGA-II algorithm performs better than the original NSGA-II algorithm since the minimum values for both total cost and the bullwhip effect are obtained in case of the modified NSGA-II. The formulated bi-objective problem is new to the research community. The minimization of bullwhip effect has never been considered in a multi-objective optimization before. Besides crossover operator applied to the fuzzy variable and the mutation operator are newly introduced operators.

Journal of Intelligent Manufacturing, 2013

In this paper, a hierarchical multi-agent based routing has been introduced. In dynamic situation... more In this paper, a hierarchical multi-agent based routing has been introduced. In dynamic situations, the previously planned entire optimum path may not stay optimum over time. Thus the approach in this paper routes a job to the next optimum neighboring node from the current position, instead of deciding over the entire path before the journey begins. Whenever there is a need to choose the next optimum node for routing or whenever a job enters the system, the master agent calls the worker agents. The worker agents run in parallel and return the results to the master agent. The worker agents are killed after their tasks are completed. The master agent takes decision based on the data delivered by the worker agents through a multi-criteria decision analysis technique known as PROMETHEE. A total of five worker agents are used for seven criteria and fuzzy approach is applied in a fuzzy shortest path algorithm performed by a worker agent and in fuzzy weight calculation in PROMETHEE. Three examples with three different kinds of networks have been used to show the effectiveness of the entire approach. The motivation of the idea introduced in this paper has come from the mating behavior of a spider known as Tarantula where the female spider sometimes eats the male spider just after mating.

The International Journal of Advanced Manufacturing Technology, 2013

Applied Mathematical Modelling, 2013

Abstract In this paper, we modify a Multi-Objective Evolutionary Algorithm, known as Nondominated... more Abstract In this paper, we modify a Multi-Objective Evolutionary Algorithm, known as Nondominated sorting Genetic Algorithm-II (NSGA-II) for a parallel machine scheduling problem with three objectives. The objectives are – (1) minimization of total cost due tardiness, (2) minimization of the deterioration cost and (3) minimization of makespan. The formulated problem has been solved by three Multi-Objective Evolutionary Algorithms which are: (1) the original NSGA-II (Non-dominated Sorting Genetic Algorithm–II), (2) SPEA2 (Strength Pareto Evolutionary Algorithm-2) and (3) a modified version of NSGA-II as proposed in this paper. A new mutation algorithm has also been proposed depending on the type of problem and embedded in the modified NSGA-II. The results of the three algorithms have been compared and conclusions have been drawn. The modified NSGA-II is observed to perform better than the original NSGA-II. Besides, the proposed mutation algorithm also works effectively, as evident from the experimental results.

The age of globalization has changed the traditional single-facility manufacturing to multi-facil... more The age of globalization has changed the traditional single-facility manufacturing to multi-facility manufacturing system. This paper proposes a novel multi-objective multi-facility distributed job shop scheduling problem. The objectives are-1) minimization of makespan and 2) minimization of tardiness of jobs. The proposed multi-objective problem is formulated with the aim of optimizing a set of time-related objectives in such scenario. The proposed problem has been solved by a nature-based technique and efforts have been exerted to make better use of the proposed nature based technique. A new mutation algorithm based on the mechanism of circular queue has been proposed and embedded in the proposed nature based algorithm. Experimental results show the effectiveness of the proposed solution technique for the proposed multi-objective problem.

2016 International Conference on Data Science and Engineering (ICDSE)

Supplier ranking problem is a widely discussed topic in the area of Supply Chain Management. This... more Supplier ranking problem is a widely discussed topic in the area of Supply Chain Management. This paper proposes to use a Multi-Criteria Decision Analysis technique, TOPSIS for ranking suppliers. Modified Triangular Fuzzy TOPSIS is proposed for ranking the suppliers. However the novelty of this paper lies in the treatment of the criteria as considered in this paper. Some of the criteria are considered to be essential and thus are used always. The uses of the remaining criteria are probabilistic since they may or may not be used depending on the situation and the set of alternative suppliers considered. A numerical problem shows the successful application of such idea and shows that such idea can be implemented.

Production and Operations Analysis, 2019

This paper applies a routing strategy based on Tarantula Mating Behavior as proposed by the autho... more This paper applies a routing strategy based on Tarantula Mating Behavior as proposed by the authors, Bandyopadhyay and Bhattacharya [1], on a manufacturing network. The particular behavior which is of interest is that the female Tarantula spider sometimes eats the male Tarantula just after mating for satisfying immediate need for food or for genetic purpose. This interesting behavior has been simulated with the help of a hierarchical multi-agent based framework where the master agent at the top of the hierarchy takes the final decision with the help of PROMETHEE multi-criteria decision analysis technique, based on the data for various criteria as delivered by the worker agents at the leaf level of the hierarchy. Fuzzy orientation has been added to the measurement for one of the criteria and in the calculation of PROMETHEE decision analysis technique. The strategy has been applied successfully on a manufacturing network.

Production and Operations Analysis, 2019

Production and Operations Analysis, 2019

A very interesting behavior as observed by author for Tarantula spider is that the female spider ... more A very interesting behavior as observed by author for Tarantula spider is that the female spider sometimes eats the male spider just after their mating in order to immediate need for food. This strange behavior has been used to propose a multi-agent and multi-criteria fuzzy routing strategy to be applied in manufacturing situations. A hierarchical structure of agents has been considered where the worker agents at the leaf level calculate shortest paths, congestion in a path, number of intermediate nodes and identify deadlock condition in the network. A master agent at the top of the hierarchy controls them. Fuzzy theory concepts have been used in case of shortest path calculation and in the calculations for PROMETHEE multi-criteria decision analysis. A network instance has used in order to implement the strategy as proposed in this research study.

2017 Second International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2017

This paper proposes fuzzy probabilistic TOPSIS outranking multi-criteria decision making techniqu... more This paper proposes fuzzy probabilistic TOPSIS outranking multi-criteria decision making technique and applies the proposed technique to a real-life multi-criteria case study. In many situations, selection of particular alternatives based on certain criteria found out to be uncertain. In such conflicting situations, probabilistic treatment for the alternatives is required. Since the determination of values of such probabilities is difficult and unrealistic as well, thus this paper proposes fuzzy probability values for the alternatives. The fuzzy probabilistic TOPSIS outranking technique is applied for the purpose. Numerical example through a case shows the applicability of the proposed technique.

Intelligent Information Management, 2012

Asian Journal of Research in Business Economics and Management, 2015

Stage shop scheduling is an emergent area in the field of scheduling. This paper has proposed a b... more Stage shop scheduling is an emergent area in the field of scheduling. This paper has proposed a bi-objective stage shop scheduling problem with total completion time and total tardiness of jobs, as objectives. In order to solve the proposed formulated problem, modified NSGA-II (Nondominated Sorting Genetic Algorithm – II) and modified MOPSO (Multi-Objective Particle Swarm Optimization) have been proposed. A mutation algorithm for NSGA-II and a velocity updation algorithm based on circular motion of alleles (for NSGA-II) and circular motion of particles (for MOPSO) have also been introduced and have been embedded in the proposed algorithms. The experimental results show that NSGA-II performs better than MOPSO in some aspects, whereas MOPSO performs better than NSGA-II in some other aspects.

This chapter presents an overview of various nature-based algorithms to solve multi-objective pro... more This chapter presents an overview of various nature-based algorithms to solve multi-objective problems with the particular emphasis on Multi-Objective Evolutionary Algorithms based on Genetic Algorithm. Some of the significant hybridization and the modification of the benchmark algorithms have also been discussed as well. The complexity issues have been outlined and various test problems to show the effectiveness of such algorithms have also been summarized. At the end, a brief discussion on the software packages used to model these type of algorithms are presented.

Advances in Intelligent Systems and Computing, 2013

Journal of Manufacturing Systems, 2014

Abstract In this paper, we propose the modification of an existing Multi-Objective Evolutionary A... more Abstract In this paper, we propose the modification of an existing Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm has been applied on a tri-objective problem for a two echelon serial supply chain. The objectives considered are: (1) minimization of the total cost of a two-echelon serial supply chain and (2) minimization of the variance of order quantity and (3) minimization of the total inventory. The variance of order quantity is an important factor to consider since the variance of order quantity is used to measure the bullwhip effect which is one of the performance measures of a supply chain. The supply chain under consideration is assumed to consist of buyers and supplier. The production process at the supplier is an imperfect production process and thus produces defective items. A percentage of defective items are sold at a secondary market and the remaining defective items are repaired. We have introduced a mutation algorithm which has been embedded in the proposed algorithm. Since the proposed mutation algorithm is performed over the entire population, thus the mutation algorithm has caused the modification of the parts of the original NSGA-II. The results of the modified algorithm have been compared with those of the original NSGA-II and SPEA2 (Strength Pareto Evolutionary Algorithm 2) evolutionary algorithms for varying values of probability of crossover. The experimental results show that the proposed algorithm performs significantly better than the original NSGA-II and SPEA2.

Journal of Intelligent Manufacturing, 2011

This paper minimizes the value of total cost and bullwhip effect in a supply chain. The objective... more This paper minimizes the value of total cost and bullwhip effect in a supply chain. The objectives have been achieved through developing a new multi-objective formulation for minimizing the total cost and minimizing the bullwhip effect of a two-echelon serial supply chain. A new crossover algorithm for a fuzzy variable and a new mutation algorithm have also been proposed while applying Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to the proposed problem. The formulated problem has been simulated by Matlab software and the results of the modified NSGA-II have been compared with those of original NSGA-II. It is found from the results that the modified NSGA-II algorithm performs better than the original NSGA-II algorithm since the minimum values for both total cost and the bullwhip effect are obtained in case of the modified NSGA-II. The formulated bi-objective problem is new to the research community. The minimization of bullwhip effect has never been considered in a multi-objective optimization before. Besides crossover operator applied to the fuzzy variable and the mutation operator are newly introduced operators.

Journal of Intelligent Manufacturing, 2013

In this paper, a hierarchical multi-agent based routing has been introduced. In dynamic situation... more In this paper, a hierarchical multi-agent based routing has been introduced. In dynamic situations, the previously planned entire optimum path may not stay optimum over time. Thus the approach in this paper routes a job to the next optimum neighboring node from the current position, instead of deciding over the entire path before the journey begins. Whenever there is a need to choose the next optimum node for routing or whenever a job enters the system, the master agent calls the worker agents. The worker agents run in parallel and return the results to the master agent. The worker agents are killed after their tasks are completed. The master agent takes decision based on the data delivered by the worker agents through a multi-criteria decision analysis technique known as PROMETHEE. A total of five worker agents are used for seven criteria and fuzzy approach is applied in a fuzzy shortest path algorithm performed by a worker agent and in fuzzy weight calculation in PROMETHEE. Three examples with three different kinds of networks have been used to show the effectiveness of the entire approach. The motivation of the idea introduced in this paper has come from the mating behavior of a spider known as Tarantula where the female spider sometimes eats the male spider just after mating.

The International Journal of Advanced Manufacturing Technology, 2013

Applied Mathematical Modelling, 2013

Abstract In this paper, we modify a Multi-Objective Evolutionary Algorithm, known as Nondominated... more Abstract In this paper, we modify a Multi-Objective Evolutionary Algorithm, known as Nondominated sorting Genetic Algorithm-II (NSGA-II) for a parallel machine scheduling problem with three objectives. The objectives are – (1) minimization of total cost due tardiness, (2) minimization of the deterioration cost and (3) minimization of makespan. The formulated problem has been solved by three Multi-Objective Evolutionary Algorithms which are: (1) the original NSGA-II (Non-dominated Sorting Genetic Algorithm–II), (2) SPEA2 (Strength Pareto Evolutionary Algorithm-2) and (3) a modified version of NSGA-II as proposed in this paper. A new mutation algorithm has also been proposed depending on the type of problem and embedded in the modified NSGA-II. The results of the three algorithms have been compared and conclusions have been drawn. The modified NSGA-II is observed to perform better than the original NSGA-II. Besides, the proposed mutation algorithm also works effectively, as evident from the experimental results.

The age of globalization has changed the traditional single-facility manufacturing to multi-facil... more The age of globalization has changed the traditional single-facility manufacturing to multi-facility manufacturing system. This paper proposes a novel multi-objective multi-facility distributed job shop scheduling problem. The objectives are-1) minimization of makespan and 2) minimization of tardiness of jobs. The proposed multi-objective problem is formulated with the aim of optimizing a set of time-related objectives in such scenario. The proposed problem has been solved by a nature-based technique and efforts have been exerted to make better use of the proposed nature based technique. A new mutation algorithm based on the mechanism of circular queue has been proposed and embedded in the proposed nature based algorithm. Experimental results show the effectiveness of the proposed solution technique for the proposed multi-objective problem.

2016 International Conference on Data Science and Engineering (ICDSE)

Supplier ranking problem is a widely discussed topic in the area of Supply Chain Management. This... more Supplier ranking problem is a widely discussed topic in the area of Supply Chain Management. This paper proposes to use a Multi-Criteria Decision Analysis technique, TOPSIS for ranking suppliers. Modified Triangular Fuzzy TOPSIS is proposed for ranking the suppliers. However the novelty of this paper lies in the treatment of the criteria as considered in this paper. Some of the criteria are considered to be essential and thus are used always. The uses of the remaining criteria are probabilistic since they may or may not be used depending on the situation and the set of alternative suppliers considered. A numerical problem shows the successful application of such idea and shows that such idea can be implemented.