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1 – 2 of 2Iman Rastgar, Javad Rezaeian, Iraj Mahdavi and Parviz Fattahi
The purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize…
Abstract
Purpose
The purpose of this study is to propose a new mathematical model that integrates strategic decision-making with tactical-operational decision-making in order to optimize production and scheduling decisions.
Design/methodology/approach
This study presents a multi-objective optimization framework to make production planning, scheduling and maintenance decisions. An epsilon-constraint method is used to solve small instances of the model, while new hybrid optimization algorithms, including multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm, multi-objective harmony search and improved multi-objective harmony search (IMOHS) are developed to address the high complexity of large-scale problems.
Findings
The computational results demonstrate that the metaheuristic algorithms are effective in obtaining economic solutions within a reasonable computational time. In particular, the results show that the IMOHS algorithm is able to provide optimal Pareto solutions for the proposed model compared to the other three algorithms.
Originality/value
This study presents a new mathematical model that simultaneously determines green production planning and scheduling decisions by minimizing the sum of the total cost, makespan, lateness and energy consumption criteria. Integrating production and scheduling of a shop floor is critical for achieving optimal operational performance in production planning. To the best of the authors' knowledge, the integration of production planning and maintenance has not been adequately addressed.
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Keywords
Mohammad Javad Jafari, Elham Akhlaghi Pirposhteh, Mohadese Farhangian, Soheila Khodakarim Ardakani, Elaheh Tavakol, Somayeh Farhang Dehghan and Amin Khalilinejad
The aim of this study is to optimize the electrospinning parameters used in the production process of polyvinyl chloride (PVC) nanofibers.
Abstract
Purpose
The aim of this study is to optimize the electrospinning parameters used in the production process of polyvinyl chloride (PVC) nanofibers.
Design/methodology/approach
The response surface methodology (RSM) was used to determine the experimental design. The 30 nanofiber prototypes candidates were electrospun using a needle-based electrospinning machine. PVC polymer, N-dimethyl formamide and tetrahydrofuran solvents were used to prepare the electrospinning solution.
Findings
The electrospun nanofibers had a mean diameter of 386 ± 136.57 nm, in the range of 200−412 nm. The mean porosity was 31.60 ± 6.37% in the range of 15.33−41.53%. The webs made from electrospun nanofibers had a mean pressure loss of 194.23 ± 47.7 pa in the range of 124−300 pa. The highest statistically significant correlation was observed between solution concentration and nanofiber diameter (r = 0.756, p < 0.05).
Originality/value
The optimal electrospinning parameters were determined to be: a solution concentration of 11 weight percent, a voltage of 16.5 kV, a needle-collector distance of 13.5 cm and an electrospinning duration of 4 h.
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