Laya Olfat; Maghsod Amiri; Ahmad Jafarian
Abstract
Cross-docking is one of the lean logistics tools that is used for uniting the shipments during the loops replacement. Cross-docking is the process of product movement form distribution centers without storage function. Vehicle routing problem in Cross-Dock external environment has much influence on cross-dock ...
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Cross-docking is one of the lean logistics tools that is used for uniting the shipments during the loops replacement. Cross-docking is the process of product movement form distribution centers without storage function. Vehicle routing problem in Cross-Dock external environment has much influence on cross-dock costs. This paper provides a model for minimizing total distance traveled by vehicles in the external environment of a cross-dock. In this paper, Vehicles routes was modeled with capacitated vehicle routing problem (CVRP) and genetic algorithm (GA) was used to solve the model. To validate responses obtained by GA, simulated annealing (SA) was used. Also, to evaluate the efficacy of two algorithms (SA & GA) in different CVRP problems in cross-dock, 10 problems with different dimensions are evaluated. The results show that in problems with smaller size GA is more efficient, whereas in large size problems SA is more efficient
Hossein Khanaki; Mahdi Azizmohammadi; Masoud Vakili; Saeed Khan Mohammadian
Volume 11, Issue 30 , October 2014, , Pages 153-179
Abstract
AbstractIn this paper, the critical parameters of a method of welding with shieldinggas arc welding (GMAW) are discussed; this method is an important processin creating high quality metal permanent connections in various industries,including the automobile industry to improve the quality of stemdiameter ...
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AbstractIn this paper, the critical parameters of a method of welding with shieldinggas arc welding (GMAW) are discussed; this method is an important processin creating high quality metal permanent connections in various industries,including the automobile industry to improve the quality of stemdiameter welding parameters. One of the most useful techniques for modelingand solving the problems is Response Surface Method. In this paper,considering five most important factors such as speed welder, torch anglewith the work piece, electrode diameter, wire speed, gas consumption ,andCO2 levels as input variables, can be controlled independently from thelevel of response, the relationship between the input variables and the responsevariables were determined using linear regression. Then optimumvalue for each factor was calculated using non-linear programming model to evaluate the results obtained along with the comparison of output of theSimulation Annealing Algorithm.In this study, both qualitative and quantitative variables are considered toevaluate and optimize all response variables regarding that these variablesare not the same, and then fuzzy set theory and LP metric are used to findanswers for multi-objective optimization methods.
