Tuli Bakshi, Arindam Sinharay, Bijan Sarkar and Subir Kumar Sanyal
The purpose of this paper is to introduce a model of decision-making problem in multi-criteria optimization domain for project selection. The model is built by combining the soft…
Abstract
Purpose
The purpose of this paper is to introduce a model of decision-making problem in multi-criteria optimization domain for project selection. The model is built by combining the soft set theory and analytic hierarchical model under fuzziness. Soft set model gives us the opportunity to use parameterization properties. Here, the authors have proved that multiple alternatives can be reduced to make the selection process computationally efficient. Here, the authors illustrate the hybrid method by means of an application of the new mathematical model of soft set theory.
Design/methodology/approach
This paper is designed to excel a decision support system with multiple criteria analysis tool, analytic hierarchy process combined with soft set theory under fuzziness.
Findings
In this paper, the authors have taken four projects P1, P2, P3 and P4. As per chosen parameters of softest theory the result of the illustrative example reveals that P2 is the best project. The ranking the authors get is in the order of P2, P3, P4 and P1. The algorithm leads the authors to maximize the proper choice in the environment of imprecise information. The main advantage of this method compare to others is that this hybrid method is very simple in terms of calculation and the computational complexity of the proposed algorithm is low.
Originality/value
This proposed decision support strategy for an intended project manager helped to take decision in the perspective environment.
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Amitava Ray, Bijan Sarkar and Subir Sanyal
The aim of this paper is to develop and demonstrate an outsourcing decision model in which constraint resource prevents the throughput of the organization.
Abstract
Purpose
The aim of this paper is to develop and demonstrate an outsourcing decision model in which constraint resource prevents the throughput of the organization.
Design/methodology/approach
An integrated model is proposed by incorporating the weighted product model (WPM) of AHP in estimating the priority of each product in a multi‐product constraint resource environment. A numerical example is presented to demonstrate the effectiveness of this model. The outsourcing decision model compares four alternatives: Standard cost accounting, standard theory‐of‐constraints (TOC), LP analysis and an original solution.
Findings
The numerical results show that the proposed model is superior and more realistically optimizes resource allocation and measures the performance of the model.
Research limitations/implications
This research is limited to the production processes that do not have multiple constraints.
Practical implications
This research is applicable to the companies which produce multi‐products in a situation in which market demand exceed the company's production capacity.
Originality/value
This is the first time that the WPM of AHP/TOC has been used to maximize the product throughput. Instead of calculating $return per constraint minute, it decides the priority of product that maximizes the product throughput in the constraint resource environment. It makes a significant contribution to the manufacturing organization where one can compare the financial performance of the organization by selecting the right decision model.
Details
Keywords
Amitava Ray, Bijan Sarkar and Subir Sanyal
The purpose of this paper is to develop and demonstrate an outsourcing model in which constraint resource prevents the throughput of the organization.
Abstract
Purpose
The purpose of this paper is to develop and demonstrate an outsourcing model in which constraint resource prevents the throughput of the organization.
Design/methodology/approach
The paper proposes an integrated model by combining the Hurwicz criterion, the theory‐of‐constraints (TOC) and linear programming (LP) into a single evaluation model in a multi‐product constraint resource environment. A case study is presented to demonstrate the effectiveness of this model. The decision model compares four alternatives: standard cost accounting, standard TOC, LP analysis, and our own solution, which is an approach that combines TOC, LP, and the Hurwicz criterion.
Findings
The numerical results show that this model is superior and more realistically optimizes resource allocation and measures the performance of the model.
Research limitations/implications
This research is limited to the production processes that do not have multiple constraints.
Originality/value
This is the first time that the integrated model comprising of Hurwicz‐TOC‐LP model has been used to maximize the product throughput. Instead of calculating $ return per constraint minute, this method decides the priority of product and resource center that maximizes the product throughput in the constraint resource environment. It makes a significant contribution to the manufacturing organization where one can compare the financial performance of the organization by selecting the right decision model.
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Keywords
Amitava Ray, Bijan Sarkar and Subir Kumar Sanyal
Cost estimation based on expert's judgment is not an ideal approach, since human decisions are usually determined according to general attributes of limited and unstructured…
Abstract
Purpose
Cost estimation based on expert's judgment is not an ideal approach, since human decisions are usually determined according to general attributes of limited and unstructured experience. The purpose of this paper is to develop a generic model of intelligence and cognitive science‐based method that can play an active role in process cost prediction within the shortest possible time.
Design/methodology/approach
In this paper, an intelligent system was conceived for prediction of total process cost of the product. The system is based on the concept of case‐based reasoning. It is a method for solving problems by making use of previous (source cases), similar situations and reusing information and knowledge about such situations. The source case data are generated by Taguchi technique and the cost function calculates the corresponding cost of each experiment in the economic time scale. The target case consists of the process variables whose cost needs to be determined. The cost for the source cases, consisting of the process variables of the already manufactured products are known in priori. The system calculates the similarities between the source cases and target cases and calculates the optimum cost. The fuzzy‐C‐means clustering method provides the model connecting the process parameters with total costs searched for.
Findings
The results show that the quality of predictions made by the intelligent system is comparable to the quality assured by the experienced expert. The proposed expert system is superior to traditional cost accounting system and assists inexperienced users in predicting the optimum process cost within the shortest possible time.
Research limitations/implications
The research was limited to the traditional machining process.
Practical implications
The paper can be applied to any process industry and will have immense practical value.
Originality/value
This is the first time an expert system has been developed for the process industry that can calculate the process cost within a few days or a few hours before making an offer to a buyer.
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Amitava Ray, Bijan Sarkar and Subir Kumar Sanyal
The primary aim in this paper is to develop and demonstrate a theory of constraints (TOC) model in which constraint resource prevents the throughput of the organization.
Abstract
Purpose
The primary aim in this paper is to develop and demonstrate a theory of constraints (TOC) model in which constraint resource prevents the throughput of the organization.
Design/methodology/approach
In this paper, the authors propose an integrated model by combining Laplace criterion and TOC into a single evaluation model in a multiproduct constraint resource environment. A case study is illustrated to demonstrate the effectiveness of this model. The outsourcing decision model compares three alternatives: standard cost accounting, standard theory‐of‐constraints, and our own solution.
Findings
The numerical results show that the new approach is superior to Standard cost accounting and Theory of Constraints and presents a more realistic state of optimum allocation of resources and measures the performance of the model.
Research limitations/implications
This research is limited to the production processes that do not have multiple constraints.
Originality/value
This is the first time that the integrated model comprising of Laplace‐TOC model has been used to maximize the product throughput. Instead of calculating $return per constraint minute, this method decides the priority of product that maximizes the product throughput in the constraint resource environment. It makes a significant contribution to the manufacturing Organization where one can compare the financial performance of the Organization by selecting the right decision model.