Harun Aydilek - Academia.edu (original) (raw)
Papers by Harun Aydilek
Journal of Economics, Jun 9, 2020
Restricted until 1 July 2010. Recursive utility functions control the investors relative risk ave... more Restricted until 1 July 2010. Recursive utility functions control the investors relative risk aversion (RRA) and elasticity of intertemporal substitution (EIS) by different parameters. They are generalization of expected utility functions in which the RRA and the EIS are controlled by the same parameter. This is widely discussed in the empirical literature. Also, the timing of the resolution of uncertainty matters in recursive setting. Recursive utility functions are widely used in the literature in order to explain many macroeconomic issues like the equity premium puzzle, risk free rate puzzle, and stock market participation. We want to have a deep understanding about the effects and relations of the model parameters. We use the Epstein-Zin preferences on a binomial tree and find the analytical closed form solution for the optimal allocations in consumption, risk free and risky assets. We give numerical results for the effects of model parameters. Numerical results show that the de...
International Journal of Industrial Engineering Computations, 2022
We consider a no-wait m-machine flowshop scheduling problem which is common in different manufact... more We consider a no-wait m-machine flowshop scheduling problem which is common in different manufacturing industries such as steel, pharmaceutical, and chemical. The objective is to minimize total tardiness since it minimizes penalty costs and loss of customer goodwill. We also consider the performance measure of total completion time which is significant in environments where reducing holding cost is important. We consider both performance measures with the objective of minimizing total tardiness subject to the constraint that total completion time is bounded. Given that the problem is NP-hard, we propose an algorithm. We conduct extensive computational experiments to compare the performance of the proposed algorithm with those of three well performing benchmark algorithms in the literature. Computational results indicate that the proposed algorithm reduces the error of the best existing benchmark algorithm by 88% under the same CPU times. The results are confirmed by extensive statis...
Applied Mathematics and Computation, 2012
Proceedings of the International Conference on Industrial Engineering and Operations Management
International Journal of Industrial Engineering Computations
We address a manufacturing environment with the no-wait constraint which is common in industries ... more We address a manufacturing environment with the no-wait constraint which is common in industries such as metal, plastic, and semiconductor. Setup times are modelled as uncertain with the objective of minimizing maximum lateness which is an important performance measure for customer satisfaction. This problem has been addressed in scheduling literature for the two-machine no-wait flowshop where dominance relations were presented. Recently, another dominance relation was presented and shown to be about 90% more efficient than the earlier ones. In the current paper, we propose two new dominance relations, which are less restrictive than the earlier ones in the literature. The new dominance relations are shown to be 140% more efficient than the most recent one in the literature. As the level of uncertainty increases, the newly proposed dominance relation performs better, which is another strength of the newly proposed dominance relation. Moreover, we also propose constructive heuristics...
World Academy of Science, Engineering and Technology, International Journal of Industrial and Manufacturing Engineering, 2015
World Academy of Science, Engineering and Technology, International Journal of Mathematical and Computational Sciences, 2016
Engineering Optimization, 2020
Journal of Industrial & Management Optimization, 2017
Applied Mathematics and Computation, 2020
Journal of Economics and Finance, 2019
Journal of Economics and Finance, 2018
International Journal of Production Research, 2017
This paper addresses a two-stage assembly flowshop scheduling problem with the objective of minim... more This paper addresses a two-stage assembly flowshop scheduling problem with the objective of minimising maximum tardiness where set-up times are considered as separate from processing times. The performance measure of maximum tardiness is important for some scheduling environments, and hence, it should be taken into account while making scheduling decisions for such environments. Given that the problem is strongly NP-hard, different algorithms have been proposed in the literature. The algorithm of Self-Adaptive Differential Evolution (SDE) performs as the best for the problem in the literature. We propose a new hybrid simulated annealing and insertion algorithm (SMI). The insertion step, in the SMI algorithm, strengthens the exploration step of the simulated annealing algorithm at the beginning and reinforces the exploitation step of the simulated annealing algorithm towards the end. Furthermore, we develop several dominance relations for the problem which are incorporated in the proposed SMI algorithm. We compare the performance of the proposed SMI algorithm with that of the best existing algorithm, SDE. The computational experiments indicate that the proposed SMI algorithm performs significantly better than the existing SDE algorithm. More specifically, under the same CPU time, the proposed SMI algorithm, on average, reduces the error of the best existing SDE algorithm over 90%, which indicates the superiority of the proposed SMI algorithm.
European Journal of Operational Research, 2018
Applied Mathematical Modelling, 2017
Journal of Industrial and Production Engineering, 2016
The objective of minimizing the number of tardy jobs is important as it is directly related to th... more The objective of minimizing the number of tardy jobs is important as it is directly related to the percentage of on-time shipments, which is often used to rate managers’ performance in many manufacturing environments. To the best of our knowledge, the assembly flowshop scheduling problem with this objective has not been addressed so far, and thus is addressed in this paper. Given that the problem is NP-hard, different heuristics are proposed for the problem in this paper. The proposed heuristics are genetic algorithm (GA), improved genetic algorithm (IGA), simulated annealing algorithm with three different neighborhood structures (SA-1, SA-2, SA-3), Dhouib et al.’s simulated annealing algorithm (DSA), and an improved cloud theory-based simulated annealing algorithm (CSA). The heuristics are evaluated based on extensive computational experiments and all the heuristics were run for the same computational time for a fair comparison. The experiments reveal that the overall average errors of DSA, GA, IGA, CSA, SA-1, SA-2, SA-3 were 20.53, 13.49, 11.64, 3.27, 2.81, 1.92, and 0.56, respectively. Therefore, the proposed heuristic of SA-3 reduces the error of DSA, GA, IGA, CSA, SA-1, SA-2 by about 97, 96, 95, 83, 80, and 71%, respectively. All the results are statistically confirmed.
We first investigate a household's asset allocation, housing and consumption decisions with a... more We first investigate a household's asset allocation, housing and consumption decisions with a multi-period model under recursive utility function. We obtain both the analytical and numerical solutions for the optimal policies. We focus just on the period after retirement. In light of the empirical evidence that the elderly people do not down-size or liquidate their housing, we assume that the household buys a house initially and then keeps it until he dies. Our analysis indicates that the composition of the liquid portfolio between stocks and bonds do not depend on the elasticity of intertemporal substitution or the weight of housing in utility parameters. We find that optimal decisions of the household depend on intertemporal elasticity of substitution, risk aversion, weight of housing in utility and characteristics of the financial assets. Our calibrated model can generate empirically documented consumption patterns of the elderly homeowners. Second, we analyze and quantify th...
Journal of Economics, Jun 9, 2020
Restricted until 1 July 2010. Recursive utility functions control the investors relative risk ave... more Restricted until 1 July 2010. Recursive utility functions control the investors relative risk aversion (RRA) and elasticity of intertemporal substitution (EIS) by different parameters. They are generalization of expected utility functions in which the RRA and the EIS are controlled by the same parameter. This is widely discussed in the empirical literature. Also, the timing of the resolution of uncertainty matters in recursive setting. Recursive utility functions are widely used in the literature in order to explain many macroeconomic issues like the equity premium puzzle, risk free rate puzzle, and stock market participation. We want to have a deep understanding about the effects and relations of the model parameters. We use the Epstein-Zin preferences on a binomial tree and find the analytical closed form solution for the optimal allocations in consumption, risk free and risky assets. We give numerical results for the effects of model parameters. Numerical results show that the de...
International Journal of Industrial Engineering Computations, 2022
We consider a no-wait m-machine flowshop scheduling problem which is common in different manufact... more We consider a no-wait m-machine flowshop scheduling problem which is common in different manufacturing industries such as steel, pharmaceutical, and chemical. The objective is to minimize total tardiness since it minimizes penalty costs and loss of customer goodwill. We also consider the performance measure of total completion time which is significant in environments where reducing holding cost is important. We consider both performance measures with the objective of minimizing total tardiness subject to the constraint that total completion time is bounded. Given that the problem is NP-hard, we propose an algorithm. We conduct extensive computational experiments to compare the performance of the proposed algorithm with those of three well performing benchmark algorithms in the literature. Computational results indicate that the proposed algorithm reduces the error of the best existing benchmark algorithm by 88% under the same CPU times. The results are confirmed by extensive statis...
Applied Mathematics and Computation, 2012
Proceedings of the International Conference on Industrial Engineering and Operations Management
International Journal of Industrial Engineering Computations
We address a manufacturing environment with the no-wait constraint which is common in industries ... more We address a manufacturing environment with the no-wait constraint which is common in industries such as metal, plastic, and semiconductor. Setup times are modelled as uncertain with the objective of minimizing maximum lateness which is an important performance measure for customer satisfaction. This problem has been addressed in scheduling literature for the two-machine no-wait flowshop where dominance relations were presented. Recently, another dominance relation was presented and shown to be about 90% more efficient than the earlier ones. In the current paper, we propose two new dominance relations, which are less restrictive than the earlier ones in the literature. The new dominance relations are shown to be 140% more efficient than the most recent one in the literature. As the level of uncertainty increases, the newly proposed dominance relation performs better, which is another strength of the newly proposed dominance relation. Moreover, we also propose constructive heuristics...
World Academy of Science, Engineering and Technology, International Journal of Industrial and Manufacturing Engineering, 2015
World Academy of Science, Engineering and Technology, International Journal of Mathematical and Computational Sciences, 2016
Engineering Optimization, 2020
Journal of Industrial & Management Optimization, 2017
Applied Mathematics and Computation, 2020
Journal of Economics and Finance, 2019
Journal of Economics and Finance, 2018
International Journal of Production Research, 2017
This paper addresses a two-stage assembly flowshop scheduling problem with the objective of minim... more This paper addresses a two-stage assembly flowshop scheduling problem with the objective of minimising maximum tardiness where set-up times are considered as separate from processing times. The performance measure of maximum tardiness is important for some scheduling environments, and hence, it should be taken into account while making scheduling decisions for such environments. Given that the problem is strongly NP-hard, different algorithms have been proposed in the literature. The algorithm of Self-Adaptive Differential Evolution (SDE) performs as the best for the problem in the literature. We propose a new hybrid simulated annealing and insertion algorithm (SMI). The insertion step, in the SMI algorithm, strengthens the exploration step of the simulated annealing algorithm at the beginning and reinforces the exploitation step of the simulated annealing algorithm towards the end. Furthermore, we develop several dominance relations for the problem which are incorporated in the proposed SMI algorithm. We compare the performance of the proposed SMI algorithm with that of the best existing algorithm, SDE. The computational experiments indicate that the proposed SMI algorithm performs significantly better than the existing SDE algorithm. More specifically, under the same CPU time, the proposed SMI algorithm, on average, reduces the error of the best existing SDE algorithm over 90%, which indicates the superiority of the proposed SMI algorithm.
European Journal of Operational Research, 2018
Applied Mathematical Modelling, 2017
Journal of Industrial and Production Engineering, 2016
The objective of minimizing the number of tardy jobs is important as it is directly related to th... more The objective of minimizing the number of tardy jobs is important as it is directly related to the percentage of on-time shipments, which is often used to rate managers’ performance in many manufacturing environments. To the best of our knowledge, the assembly flowshop scheduling problem with this objective has not been addressed so far, and thus is addressed in this paper. Given that the problem is NP-hard, different heuristics are proposed for the problem in this paper. The proposed heuristics are genetic algorithm (GA), improved genetic algorithm (IGA), simulated annealing algorithm with three different neighborhood structures (SA-1, SA-2, SA-3), Dhouib et al.’s simulated annealing algorithm (DSA), and an improved cloud theory-based simulated annealing algorithm (CSA). The heuristics are evaluated based on extensive computational experiments and all the heuristics were run for the same computational time for a fair comparison. The experiments reveal that the overall average errors of DSA, GA, IGA, CSA, SA-1, SA-2, SA-3 were 20.53, 13.49, 11.64, 3.27, 2.81, 1.92, and 0.56, respectively. Therefore, the proposed heuristic of SA-3 reduces the error of DSA, GA, IGA, CSA, SA-1, SA-2 by about 97, 96, 95, 83, 80, and 71%, respectively. All the results are statistically confirmed.
We first investigate a household's asset allocation, housing and consumption decisions with a... more We first investigate a household's asset allocation, housing and consumption decisions with a multi-period model under recursive utility function. We obtain both the analytical and numerical solutions for the optimal policies. We focus just on the period after retirement. In light of the empirical evidence that the elderly people do not down-size or liquidate their housing, we assume that the household buys a house initially and then keeps it until he dies. Our analysis indicates that the composition of the liquid portfolio between stocks and bonds do not depend on the elasticity of intertemporal substitution or the weight of housing in utility parameters. We find that optimal decisions of the household depend on intertemporal elasticity of substitution, risk aversion, weight of housing in utility and characteristics of the financial assets. Our calibrated model can generate empirically documented consumption patterns of the elderly homeowners. Second, we analyze and quantify th...