Constructing a fuzzy flow-shop sequencing model based on statistical data

AbstractThis study investigated an approach for incorporating statistics with fuzzy sets in the flow-shop sequencing problem. This work is based on the assumption that the precise value for the processing time of each job is unknown, but that some sample data are available. A combination of statistics and fuzzy sets provides a powerful tool for modeling and solving this problem. Our work intends to extend the crisp flow-shop sequencing problem into a generalized fuzzy model that would be useful in practical situations. In this study, we constructed a fuzzy flow-shop sequencing model based on statistical data, which uses level (1−α,1−β) interval-valued fuzzy numbers to represent the unknown job processing time. Our study shows that this fuzzy flow-shop model is an extension of the crisp flow-shop problem and the results obtained from the fuzzy flow-shop model provides the same job sequence as that of the crisp problem

Identification of Supply Chains Based on Input-Output Data

The paper focuses on supply chain modeling issues, namely how subspace identification techniques can be used to characterize the strength of relations between certain system parameters. This might be useful when no knowledge about the internal workings or inner structure of the system is available, thus only blackbox like approaches can be utilized. Here let us show how supply chains can be identified and modeled by deterministic linear state space models and how the accuracy of the identified model reflects the relation between certain system parameters

Two Stage Fuzzy Flow Shop Scheduling to Minimize Rental Cost with Job – Block Criteria

In this paper we consider two stage flow shop scheduling to minimize the total rental cost of machines for n-jobs in fuzzy environment. The processing time of jobs and setup time for machines are uncertain. The fuzzy triangular membership function is used to describe uncertain processing times and setup times. Further, the restriction of equivalent job-block on job processing is also considered. The objective of the paper is to develop a new heuristic algorithm to minimize the rental cost of machines which is simple and straight forward. A numerical illustration explaining the computational process of the proposed algorithm is also given. Keywords: fuzzy processing time, fuzzy setup time, rental cost, average high ranking, utilization time and equivalent job –bloc

A Mathematical Model for a Flow Shop Scheduling Problem with Fuzzy Processing Times

Abstract This paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable makespan and the probability of minimizing the makespan. These criteria can be considered for fuzzy problems as well. In this paper, we propose a solution for the fuzzy model by the use of fuzzy logic based on developing the model presented by MacCahon [18]

A Mathematical Model for a Flow Shop Scheduling Problem with Fuzzy Processing Times

This paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable makespan and the probability of minimizing the makespan. These criteria can be considered for fuzzy problems as well. In this paper, we propose a solution for the fuzzy model by the use of fuzzy logic based on developing the model presented by MacCahon [18]

An extension of the ratio system approach of MOORA method for group decision-making based on interval-valued triangular fuzzy numbers

Decision-making in fuzzy environment is often a very complex, especially when related to predictions and assessments. The Ratio system approach of the MOORA method and Intervalvalued fuzzy numbers have already proved themselves as the effective tools for solving complex decision-making problems. Therefore, in this paper an extension of the Ratio system approach of the MOORA method, which allows a group decision-making as well as the use of interval-valued triangular fuzzy numbers, is proposed. Interval-fuzzy numbers are rather complex, and therefore, they are not practical for direct assigning performance ratings. For this reason, in this paper it has also been suggested the approach which allows the expression of individual performance ratings using crisp, interval or fuzzy numbers, and their further transformation into the group performance ratings, expressed in the form of interval-valued triangular fuzzy numbers, which provide greater flexibility and reality compared to the use of linguistic variables. Finally, in this paper the weighted averaging operator was proposed for defuzzification of interval-valued triangular fuzzy numbers. First published online: 21 Sep 201