Journal of Optimization
http://www.i-scholar.in/index.php/JOpT
Journal of Optimization is a peer-reviewed, open access journal that publishes original research articles as well as review articles related to all aspects of optimization.en-USjopti@hindawi.com (Dr. Adil M. Bagirov)jopti@hindawi.com (Dr. Adil M. Bagirov)Fri, 06 May 2016 05:44:40 +0000OJS 2.4.2.0http://blogs.law.harvard.edu/tech/rss60Optimization of Conductive Thin Film Epoxy Composites Properties using Desirability Optimization Methodology
http://www.i-scholar.in/index.php/JOpT/article/view/99137
Multiwalled carbon nanotubes (MWCNTs)/epoxy thin film nanocomposites were prepared using spin coating technique. The effects of process parameters such as sonication duration (5–35 min) and filler loadings (1-2 vol%) were studied using the design of experiment (DOE). Full factorial design was used to create the design matrix for the two factors with three-level experimentation, resulting in a total of 9 runs (3<sup>2</sup>) of experimentation. Response surface methodology (RSM) combined with E.C. Harrington's desirability function called desirability optimization methodology (DOM) was used to optimize the multiple properties (tensile strength, elastic modulus, elongation at break, thermal conductivity, and electrical conductivity) of MWCNTs/epoxy thin film composites. Based on response surface analysis, quadratic model was developed. Analysis of variance (ANOVA), 𝑅-squared (𝑅-Sq), and normal plot of residuals were applied to determine the accuracy of the models. The range of lower and upper limits was determined in an overlaid contour plot. Desirability function was used to optimize themultiple responses of MWCNTs/epoxy thin film composites. A global solution of 12.88 min sonication and 1.67 vol% filler loadings was obtained to have maximum desired responses with composite desirability of 1.C. P. Khor, Mariatti Bt. Jaafar, Sivakumar Ramakrishnanhttp://www.i-scholar.in/index.php/JOpT/article/view/99137A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems
http://www.i-scholar.in/index.php/JOpT/article/view/99150
Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and 𝑁𝑃-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.Hamed Piroozfard, Kuan Yew Wong, Adnan Hassanhttp://www.i-scholar.in/index.php/JOpT/article/view/99150A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism
http://www.i-scholar.in/index.php/JOpT/article/view/99153
The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.Farhad Ghassemi Tarihttp://www.i-scholar.in/index.php/JOpT/article/view/99153