Facility location, layout, design, and materials handling
H. Jafari; M. Ehsanifar; A. Sheykhan
Abstract
The Quadratic Assignment Problem (QAP) is one of the problems of combinatorial optimization belonging to the NP-hard problems’ class and has a wide application in the placement of facilities. Thus far, many efforts have been made to solve this problem and countless algorithms have been developed ...
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The Quadratic Assignment Problem (QAP) is one of the problems of combinatorial optimization belonging to the NP-hard problems’ class and has a wide application in the placement of facilities. Thus far, many efforts have been made to solve this problem and countless algorithms have been developed to achieve the optimal solutions; one of which is the Simulated Annealing (SA) algorithm. This paper aims at finding a suitable layout for the facilities of an industrial workshop by using a Developed Simulated Annealing (DSA) method.
Facility location, layout, design, and materials handling
N. Moradi; Sh. Shadrokh
Abstract
Construction Site Layout Planning (CSLP) is an important problem because of its impact on time, cost, productivity, and safety of the projects. In this paper, CSLP is formulated by the Quadratic Assignment Problem (QAP). At first, two case studies including equal and un-equal area facilities are solved ...
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Construction Site Layout Planning (CSLP) is an important problem because of its impact on time, cost, productivity, and safety of the projects. In this paper, CSLP is formulated by the Quadratic Assignment Problem (QAP). At first, two case studies including equal and un-equal area facilities are solved by the simulated annealing optimization algorithm. Then, the obtained results are compared with the other papers. The comparisons show that the proposed Simulated Annealing (SA) is as efficient as ACO, PSO, CBO, ECBO, WOA, WOA-CBO, and ACO-PA which have been proposed by other papers for the same problems. As a result, the comparisons show that SA is as capable as other meta-heuristics of solving the combinatorial optimization problems like CSLP, while the hardware properties and computational times have been compared. Besides the comparisons, the design of experiments shows the relationship between each SA parameter and the computational time of the algorithm. Also, the history of convergence of the proposed SA indicates the high speed of reaching the optimal solution and the artificial intelligence of the proposed SA.
Kh. Pichka; B. Ashjari; A. Ziaeifar; P. Nickbeen
Volume 3, Issue 2 , May 2014, , Pages 46-55
Abstract
MDOVRP is a variant of classical VRP, which seeks to find a set of non-depot returning vehicle routes dispatching form several depots. A new integer linear programming model is presented considering limited number of vehicles at each depot. Randomly generated smallsized MDOVRPs are solved for validation ...
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MDOVRP is a variant of classical VRP, which seeks to find a set of non-depot returning vehicle routes dispatching form several depots. A new integer linear programming model is presented considering limited number of vehicles at each depot. Randomly generated smallsized MDOVRPs are solved for validation and verification of the proposed model. Due to the complexity of the problem, a simulated annealing algorithm (SA) is developed for medium and large-sized MDVRPs’ benchmarks.
F. Rajabi; S.E. Najafi; M. Hajiaghaei-Keshteli; S. Molla-Alizadeh-Zavardehi
Volume 2, Issue 3 , September 2013, , Pages 24-34
Abstract
In the present paper the step fixed charge transportation problem under uncertainty, particularly when variable and fixed cost are given in fuzzy forms, is formulated. In order to solve the problem, two metaheuristic, simulated annealing algorithm (SA) and variable neighborhood search (VNS), are developed ...
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In the present paper the step fixed charge transportation problem under uncertainty, particularly when variable and fixed cost are given in fuzzy forms, is formulated. In order to solve the problem, two metaheuristic, simulated annealing algorithm (SA) and variable neighborhood search (VNS), are developed for this NP-hard problem. Due to the significant role of parameters and operators on the algorithm’s quality, an extensive calibration in both SA and VNS is carried out with the aid of a set of experimental design. Through extensive computational experiments, appropriate parameter values of the proposed algorithms were chosen. For this purpose, twenty eight problems with different configuration have been generated at random and then the effectiveness of the proposed algorithms was evaluated using the relative percentage deviation (RPD) method.
