Subir Kumar Sanyal

The TOC-Based Algorithm for Solving Multiple Constraint Resources

The theory of constraints (TOC) emphasizes the exploitation of resource constraints in order to increase the product throughput of an organization. The product-mix decision is one application of the five steps in the TOC. This paper considers an integrated heuristic model comprising the analytic hierarchy process (AHP) and the TOC in a decision model in which priority of product and resource center optimizes the product throughput in a multiple constraint resource environment. An AHP component allows the decision maker to incorporate tangible and intangible criteria into the decision-making process and use the priority rankings of the AHP to represent a measure of value in the TOC model. The TOC identifies the constraints and the product ranking of the AHP maximizes the product throughput in a multiple constraint resource environment. The methodology incorporates sensitivity analysis to provide the decision maker with additional information regarding the robustness of the model so that he or she can make a better decision. The model compares three alternatives: the standard TOC, Integer Linear Programming (ILP), and our own solution. The numerical result shows that the proposed approach is superior to TOC and to ILP analysis and provides a measure of the models performance.

A De Novo multi-approaches multi-criteria decision making technique with an application in performance evaluation of material handling device

We propose a De Novo MCDM model (TPOP) for precise ranking and selection.We introduce advanced version of entropy weighting method.This model (TPOP) eliminates inappropriate weights distribution.This model (TPOP) overcomes the rank reversal of the conventional approaches.The new model (TPOP) assists and guides decision makers. Application of multiple conventional approaches to a particular multi-criteria decision making (MCDM) problem often suffers rank reversal giving rise to confusion and ambiguity in appropriate decision making. To eradicate the confusion, this paper proposes a De Novo multi-approaches multi-criteria decision making method namely Technique of Precise Order Preference (TPOP). The TPOP first examines the inconsistency in the ranking order of the alternatives of a MCDM problem by using multiple conventional approaches. If inconsistency/rank reversal in ranking order of the alternatives exists then TPOP, using advanced version of entropy weighting method introduced in this research work, measures weights of the final selection values of conventional approaches. Subsequently, TPOP based on these weights and final selection values computes precise selection indices (PSI) that determines accurate ranking order for the alternatives. The proposed technique is illustrated by two real life examples on material handling device (MHD) ranking and selection problems. The first example is initially solved using five conventional integrated fuzzy multi-criteria decision making techniques (FMCDMs) whereas the second example is taken from previous researchers works. The results obtained using TPOP justify the validity, applicability and requirements of the proposed technique. The study shows that the proposed multi-approaches, multi-criteria decision making technique can be a useful and effective model in MCDM.

Multi objective performance analysis

Display Omitted A novel modified weight concept included in algorithm MOPA is unique in nature.New concept reduces inherent inaccuracy of weights significantly.MOPA can handle subjective and objective attributes; benefit and cost criteria.The algorithm MOPA fits itself in the class of applied MCDM techniques.ANOVA and SA reveal MOPA as precisely accurate and effective decision making tool. This investigation introduces multi objective performance analysis (MOPA), a novel multi-criteria decision making (MCDM) approach to solve decision problems in a supply chain. In this paper, an innovative modified weight concept is employed to modify the weights of the criteria in order to reduce the affect of the inherent inaccuracy involved with direct use of weights. Modified weight and normalized performance rating are integrated to compute modified weighted performance (MWP). Aggregate modified weighted performances (AMWP) of the alternatives are determined to evaluate benefit cost ratio (BCR) which is considered as the final selection index of the alternative. The proposed algorithm MOPA is illustrated with six real life decision problems in various stages of a supply chain to adjudge its enviable significance from the point of simplicity, feasibility and applicability. In order to ensure the compatibility, the result obtained by the proposed algorithm MOPA is compared with the proven and established MCDM methodologies TOPSIS, SAW, MOORA, ELECTRE II, and VIKOR. The comparative analysis shows that the achieved result perfectly matches with most of the cited decision problems of previous research works published in various journals. Analysis of variance (ANOVA) reveal that the modified weight concept reduces the relative dispersion of weights significantly, leads to precise decision. Sensitivity analysis (SA) and other investigations also find MOPA as a simple, robust, effective and precise decision making tool.

Warehouse location selection by fuzzy multi-criteria decision making methodologies based on subjective and objective criteria

Abstract This paper proposes three new extended fuzzy multi-criteria decision making methodologies capable of handling subjective and objective factors for the evaluation and selection of warehouse location. A warehouse location selection problem involves both subjective as well as objective criteria. The concept of fuzzy set theory is integrated with the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), Simple Additive Weight (SAW) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods to assess subjective criteria in terms of subjective factor measures. A classical normalization technique is employed to assess the objective criteria in terms of objective factor measures. Subjective factor measures and objective factor measures are integrated by the Brown and Gibson model to calculate the warehouse location selection index. The proposed methods are illustrated with two examples of warehouse location selection. A comparative study of the results and a sensitivity analysis are carried out. The study finds that the proposed methodologies are useful and effective fuzzy multi-criteria decision making tools for the evaluation and selection of warehouse location in a supply chain.

Selection of robot for automated foundry operations using fuzzy multi-criteria decision making approaches

This paper employs three Fuzzy Multi-Criteria Decision Making (FMCDM) methodologies in the evaluation and selection of robots for automated foundry operations. In the methodologies, a Fuzzy Analytical Hierarchy Process (FAHP) is integrated individually with a Fuzzy Technique for Order Preference by Similarity to the Ideal Solution (FTOPSIS), a Fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (FVIKOR) and a Complex PRoportional ASsessment method with the application of Grey systems theory (COPRAS-G). In each case, a FAHP is used to estimate the fuzzy weights of the selection criteria under consideration. FTOPSIS, FVIKOR and COPRAS-G are applied to evaluate as well as to select the robots. A real life problem of robots selection in foundry operation is cited to demonstrate and validate the applicability and potentiality of the employed methodologies. A comparative analysis of the results obtained by the methodologies is carried out. The study finds that the employed methodologies are useful, effective and sound surrogates for selecting the best robot in an FMCDM environment.

An improved theory of constraints

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

A holistic approach for production outsourcing

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.

A soft-computing approach for software project selection

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 integr...

An integrated Theory-Of-Constraints

Every software manufacturing company wants to gain higher market share with the development of their products. Evolving high quality software products will decrease the cost of R&D and increase productivity. In this aspect, proper project selection in consideration with multiple factors is very vital step. There are many mutually inclusive and exclusive factors-in combinations with vagueness. The authors have tried to depict one of such situation from analytical point of view. The main objective of this paper is to explain how quality function deployment (QFD) model is used in combining with AHP under fuzziness. The authors have proposed an integrated model determines project selection system from a economic point of view also. The proposed integrated approach identifies technical requirements followed by customer requirements.

Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

The objective of this research is to investigate the integration of Theory-Of-Constraints, analytic hierarchy process and linear programming so as to provide management with the capability of making outsourcing decision. This paper compares possible solution between standard cost accounting, standard Theory-Of-Constraints and an approach that combines Standard Theory-Of- Constraints - Analytic Hierarchy Process-Linear programming. Numerical results show that combined model is better than traditional model. This research is limited to the production process where there is no multiple constraints.