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For small networks, the integer model is used to study algorithm performance in terms of optimality.
Two fractional order models are compared with the integer model of traditional capacitor.
The integer model uses a number of 0 1 variables ranging from 2000 to 15,000 and gives optimum solutions in an average time of 60 seconds (for instances up to 60 clients).
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The results show that one of the integer models leads to tight bounds, and the tabu search algorithm generates high-quality solutions for large instances in short computing time.
Results show that the use of this new heuristic integrated with the exact integer model seems to be a good approach for car sequencing problems.
For larger instances we propose a heuristic approach based on a linear programming relaxation of the mixed integer model.
Furthermore, the proposed mixed integer model takes the maximum number of allowable jobs in each period which helps to maintain quality of the products.
The proposed mixed integer model is presented in the next section and considering computational complexity of the problem we propose three multi-objective optimization algorithms for solving the problems in the following section.
The first model is the integer order model of the ideal ultracapacitor.
The proposed mixed integer model is implemented in commercial optimization solver CPLEX 12.6.3.
The proposed mixed integer model was performed by GAMS and Cplex solver and was run on a processor Intel Core 2 Duo CPU running at 2 GHz with 2-GB RAM.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com