Ashwani Dhingra - Academia.edu (original) (raw)
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Papers by Ashwani Dhingra
Measuring Business Excellence, 2010
Purpose -In order to achieve excellence in manufacturing, goals like lean, economic and quality p... more Purpose -In order to achieve excellence in manufacturing, goals like lean, economic and quality production with enhanced productivity play a crucial role in this competitive environment. It also necessitates major improvements in generally three primary technical areas: variation reduction, equipment reliability, and production scheduling. Complexity of the real world scheduling problems also increases with interactive multiple decision-making criteria. This paper aims to deal with multi-objective flow shop scheduling problems, including sequence dependent set up time (SDST). The paper also aims to consider the objective of minimizing the weighted sum of total weighted tardiness, total weighted earliness and makespan simultaneously. It proposes a new heuristic-based hybrid simulated annealing (HSA) for near optimal solutions in a reasonable time.
International Journal of Advanced Operations Management, 2010
ABSTRACT Sequence dependent setup times (SDSTs) flow shop scheduling problems with due date relat... more ABSTRACT Sequence dependent setup times (SDSTs) flow shop scheduling problems with due date related performance measures have been increasing attention from managers and researchers. Most of flow shop scheduling problems is NP hard and various heuristics and metaheuristics have been developed for finding solutions in a very reasonable time. In this work, the authors have proposed hybrid genetic algorithm (HGA) for SDST flow shop scheduling problems using strong computational power of matrix laboratory (MATLAB) and robustness of metaheuristics. Four modified NEH‐based HGA have been developed and their performance has been compared with the help of a defined index for medium to large size problems. The objective function considered is minimisation of total weighted squared tardiness with due dates and weighting coefficient attached to each job. Comparison shows that the modified NEH4‐based HGA performs better for medium to large size problems. The work has been supported by the computational results and application to the cold rolling division of a steel industry.
Measuring Business Excellence, 2010
Purpose -In order to achieve excellence in manufacturing, goals like lean, economic and quality p... more Purpose -In order to achieve excellence in manufacturing, goals like lean, economic and quality production with enhanced productivity play a crucial role in this competitive environment. It also necessitates major improvements in generally three primary technical areas: variation reduction, equipment reliability, and production scheduling. Complexity of the real world scheduling problems also increases with interactive multiple decision-making criteria. This paper aims to deal with multi-objective flow shop scheduling problems, including sequence dependent set up time (SDST). The paper also aims to consider the objective of minimizing the weighted sum of total weighted tardiness, total weighted earliness and makespan simultaneously. It proposes a new heuristic-based hybrid simulated annealing (HSA) for near optimal solutions in a reasonable time.
International Journal of Advanced Operations Management, 2010
ABSTRACT Sequence dependent setup times (SDSTs) flow shop scheduling problems with due date relat... more ABSTRACT Sequence dependent setup times (SDSTs) flow shop scheduling problems with due date related performance measures have been increasing attention from managers and researchers. Most of flow shop scheduling problems is NP hard and various heuristics and metaheuristics have been developed for finding solutions in a very reasonable time. In this work, the authors have proposed hybrid genetic algorithm (HGA) for SDST flow shop scheduling problems using strong computational power of matrix laboratory (MATLAB) and robustness of metaheuristics. Four modified NEH‐based HGA have been developed and their performance has been compared with the help of a defined index for medium to large size problems. The objective function considered is minimisation of total weighted squared tardiness with due dates and weighting coefficient attached to each job. Comparison shows that the modified NEH4‐based HGA performs better for medium to large size problems. The work has been supported by the computational results and application to the cold rolling division of a steel industry.