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.
Scheduling
T. Chawasemerwa; I. W. Taifa; D. Hartmann
Abstract
Doctor scheduling is a complex, costly and time-consuming exercise. This study develops a constraint satisfaction and penalty minimisation scheduling model for meeting ‘hard constraints’ and minimises the cost of violating ‘soft constraints’, i.e. the user inputs, the total number ...
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Doctor scheduling is a complex, costly and time-consuming exercise. This study develops a constraint satisfaction and penalty minimisation scheduling model for meeting ‘hard constraints’ and minimises the cost of violating ‘soft constraints’, i.e. the user inputs, the total number of doctors to be scheduled, the maximum penalty to be met, and the minimum number of doctors to be assigned per shift. The algorithm creates a schedule which checks against all the constraints. The total schedule penalty associated with the constraint violations should be less than or equal to the user input penalty. If this condition is met, the schedule gets produced as the final and near-optimal solution. The model is managed to create a near optimal schedule with the minimal rule violations. However, it is challenging to provide a schedule with no rule violations. Such a situation is shown by the amount of computational time required to create a zero-penalty schedule, hours or even days needed to create a zero-penalty schedule. The system creates a schedule for a short period (weekly schedule) to promote flexibility; however, such a system does not promote fairness. Fairness is achieved through a cyclic schedule with rotations equal to the total number of doctors being scheduled. The system is managed to create a streamlined and flexible working environment and helped to improve the quality of healthcare. An optimization protocol can be incorporated into the system to reduce the search space and get the best optimal schedule since it is possible to get many schedules under the same user-defined parameters.
H. Mohammadi-Andargoli; R. Tavakkoli-Moghaddam; N. Shahsavari Pour; M.H. Abolhasani-Ashkezari
Volume 1, Issue 2 , Summer 2012, , Pages 10-26
Abstract
This paper addresses the permutation of a flexible job shop problem that minimizes the makespan and total idleness as a bi-objective problem. This optimization problem is an NP-hard one because a large solution space allocated to it. We use a duplicate genetic algorithm (DGA) to solve the problem, which ...
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This paper addresses the permutation of a flexible job shop problem that minimizes the makespan and total idleness as a bi-objective problem. This optimization problem is an NP-hard one because a large solution space allocated to it. We use a duplicate genetic algorithm (DGA) to solve the problem, which is developed a genetic algorithm procedure. Since the proposed DGA is working based on the GA, it often offers a better solution than the standard GA because it includes the rational and appropriate justification. The proposed DGA is used the useful features and concepts of elitism and local search, simultaneously. It provides local search for the best solution in every generation with the neighborhood structure in several stages and stores them in an external list for reuse as a secondary population of the GA. The performance of the proposed GA is evaluated by a number of numerical experiments. By comparing the results of the DGA other algorithms, we realize that our proposed DGA is efficient and appropriate for solving the given problem.
Fuzzy optimization
M. M. Tavakoli; B. Molavi; H. Shirouyehzad
Abstract
In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance ...
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In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance of human capital management, by evaluating the performance of human capital management system, managers can be aware of their organization’s status from the perspective of human capital management creation and perform corrective practices better. In this study, a method for the performance evaluation and ranking of organizational unit is presented using fuzzy DEA. Therefore in the beginning, the performance of organizational units was evaluated using fuzzy DEA and then with the use of sensitivity analysis, the most effective criteria on the efficiency of organizational units were determined. Then using the efficiency of organizational units in the best and the worst states, ranking of organizational units has been paid. Finally to examine the functionality of the proposed method, Foolad Technic Company has been chosen as a case study and the procedure has been implemented in this company.
Decision analysis and methods
H. R. Seiti; A. Behnampour; D. M. Imani; M. Houshmand
Abstract
Failure Modes and Effects Analysis (FMEA) is being widely used to detect and eliminate known and/or potential failures, problems, errors and so on from system design, process, and/or service, before they reach the customer. It can be done by calculating the risk priority number which is the product of ...
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Failure Modes and Effects Analysis (FMEA) is being widely used to detect and eliminate known and/or potential failures, problems, errors and so on from system design, process, and/or service, before they reach the customer. It can be done by calculating the risk priority number which is the product of three factors: occurrence, severity and detectability. A lot of efforts have been made to overcome the shortcomings of the crisp RPN calculation and extend it to fuzzy environment. In this study, the presented fuzzy approach allows experts to describe the variables of risk priority number using linguistic terms by applying the method of fuzzy axiomatic design (FAD). At the final part of this paper a hypothetical case study demonstrated the applicability of the FMEA model under fuzzy environment.
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