Mohammad Reza Hassani; Javad Behnamian
Abstract
The employee scheduling seeks to find an optimal schedule for employees according to the amount of demand (workload), employee availability, labor law, employment contracts, etc. The importance of this problem in improving the quality of service, health and satisfaction of employees and reducing costs, ...
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The employee scheduling seeks to find an optimal schedule for employees according to the amount of demand (workload), employee availability, labor law, employment contracts, etc. The importance of this problem in improving the quality of service, health and satisfaction of employees and reducing costs, including in hospitals, military or service centers, has encouraged researchers to study. In this regard, nurse rostering problem is a scheduling that determines the number of nurses required with different skills and the time of their services on the planning horizon. In this research, by adding the nurses' shift preferences and number of consecutive working days constraints, an attempt has been made to make the problem more realistic. The objective function of the problem is to minimize the total cost of allocating work shifts to nurses, the cost of the number of nurses required to reserve, the cost of overtime from a particular shift, the cost of underemployment from a particular shift, the cost of overtime on the planning horizon, the cost of underemployment on the planning horizon and the cost of absence shift-working and non-working days preferred by nurses. To solve problem, after modeling the problem as a mixed-nteger program and due to the complexity of the problem, the differential evolutionary algorithm is used with innovation in its crossover operator. To validate the proposed algorithm, its output was compared with the genetic algorithm. The results show that the differential evolutionary algorithm has good performance in problem-solving.Keywords: Nurse Rostering Problem, Deferential Evolution Algorithm
Javad Behnamian; Amir Afsar
Abstract
In general, numerous studies have paid a special attention to machine planning, job allocating and job sequencing in scheduling problems to optimize makespan. Due to the relation among economy, energy and environmental concerns, energy use is one of the most important issues in different systems planning. ...
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In general, numerous studies have paid a special attention to machine planning, job allocating and job sequencing in scheduling problems to optimize makespan. Due to the relation among economy, energy and environmental concerns, energy use is one of the most important issues in different systems planning. In this paper, a scheduling of heterogeneous parallel machines is studied, in which the job process speed on every machine is settable. Since there is a direct link between used energy of machines and process speed, the purpose of the paper is to minimize total used energy and tardiness-related costs in delivering customers' demand. In order to optimizing the problem, two meta-heuristic algorithms, Memetic algorithm and Genetic algorithm, are developed, finally the results of both algorithms are analyzed and then compared to each other as well as to the results of the GAMS optimization software.
Javad Behnamian; Mohammad Mehdi Bashar
Abstract
Cooperation in supply chain, due to conflicts in goals, is one the most important topics in SCM. With cooperation, players in supply chain echelons have agree with each other to play in supply chain game as a whole. To reach highest profit in the whole supply chain in cooperation condition, using game ...
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Cooperation in supply chain, due to conflicts in goals, is one the most important topics in SCM. With cooperation, players in supply chain echelons have agree with each other to play in supply chain game as a whole. To reach highest profit in the whole supply chain in cooperation condition, using game theory concept and side-contract of partnership in profits and considering marketing cost between manufacture and retailer, a cooperative multi-echelon supply chain is designed. In this paper, for the first time, mathematical modeling in fuzzy environment is presented, taking into account a discount that is approximated to the actual situation where the marketing cost is considered as triangular fuzzy number. The proposed model has been solved using Genetic algorithm (GA), simulated annealing algorithm (SA) and a hybrid algorithm based on GA-SA, for some random examples, and the model has been validated using GAMS software.
Abstract
Overally location problem could be classified as desirable facility location and undesirable facility location. In the undesirable facility location problem contrary to desirable location, facilities are located far from service receiver facilities as much as possible. The problem of locating such facilities ...
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Overally location problem could be classified as desirable facility location and undesirable facility location. In the undesirable facility location problem contrary to desirable location, facilities are located far from service receiver facilities as much as possible. The problem of locating such facilities is discussed in this paper. This research is focused on the “not in my backyard” (NIMBY) which refers to the social phenomena in which residents are opposed to locate undesirable facilities around their houses. Examples of such facilities include electric transmission lines and recycling centers. Due to the opposition typically encountered in constructing an undesirable facility, the facility planner should understand the nature of the NIMBY phenomena and consider it as a key factor in the determining facility location. A integer linear model of this problem and a Lagrange relaxation method are proposed in this research. This method relaxes up the hard constraints and adds the constraints to the objective function with a Lagrangian multiplier. To show that the Lagrangian relaxation method is computationally powerful exact solution algorithm and is capable to solve the medium-size problems, the performance of the proposed algorithm is examined by applying it to several test problems.
Javad Behnamian; Zeinab Akhavan
Abstract
Work in industrial workshops and heavy activities has effects on the health of workers and in terms of occupational hazards associated with many risks for them. Since in the industrial units there are different works in terms of ergonomic load and hardship of work, the occupational hazards can be reduced ...
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Work in industrial workshops and heavy activities has effects on the health of workers and in terms of occupational hazards associated with many risks for them. Since in the industrial units there are different works in terms of ergonomic load and hardship of work, the occupational hazards can be reduced by job rotation scheduling. In this paper, using reduction approach, the ergonomic job rotation scheduling problem (EJRP) is reduced to parallel machine scheduling problem so that its exact methods (such as branch and bound method) are used to solve the EJRP. Furthermore, according to the proposed reduction, the lower bounds for parallel machine scheduling problem also applied for branch and bound solving method. The main aim of this research is providing an optimal scheduling for job rotation by applying human factors engineering approach in order to minimize the maximum workload on the staffs
Farzaneh Adabi; Javad Behnamian
Abstract
The production routing problem (PRP) integrates vehicle routing and production planning problems. Generally, in PRPs, the impact of competitors has not been considered. Clearly, in the real world, it is no longer possible to have a monopoly market. In competitive environment, customers choose a supplier ...
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The production routing problem (PRP) integrates vehicle routing and production planning problems. Generally, in PRPs, the impact of competitors has not been considered. Clearly, in the real world, it is no longer possible to have a monopoly market. In competitive environment, customers choose a supplier based on price and quality. So in this article as a definition of quality, providing quick access to customer needs and availability are determined as the requirements of a competitive environment. Therefore, the production routing problem has been modeled with knowing the earliest and latest time of competitor demand meeting. In this way, In case of delay in supplying customers demand, the market share is lost relative to the amount of delay. The problem is modeled and it has been solved by the GAMS software. Since particle swarm optimization has been successfully applied to a variety of problems, here, to solve the problem for the large-sized instances a particle swarm optimization algorithm is also presented. To evaluate the performance of the proposed algorithm, the results with small-sized instances were compared with solutions of GAMS.
