فهرست مطالب

International Journal of Research in Industrial Engineering
Volume:5 Issue: 1, Autumn 2016

  • تاریخ انتشار: 1395/08/11
  • تعداد عناوین: 3
|
  • B. Naderi * Pages 1-15
    This paper considers the problem of university course timetabling. In this problem, there are a set of courses, lecturers and classrooms. The objective is to assign schedule courses so as to maximize the total preference of lecturer-course, lecturer-day and course-day. The paper first formulates the problem in form of linear integer programming model. Using the model and commercial software, the small sized instances are optimally solved. Then, the paper proposes three different algorithms based on imperialist competitive algorithm, simulated annealing and variable neighborhood search. The algorithms employ several novel procedures such as encoding scheme, move operator, crossing operators. The algorithms are tuned and evaluated with optimal solutions found by the model. Then, they are evaluated by comparing their performance. The results show that imperialist competitive algorithm outperforms the other algorithms.
    Keywords: University course scheduling, mathematical model, Metaheuristics
  • H. Farrokhi Asl, R. Tavakkoli Moghaddam * Pages 16-42

    This paper is an extension of the well-known vehicle routing problem (VRP) consisting of two stages. The first and second stages deal with the vehicle routing and transportation problems, respectively. Waste collection is one of the applications of the considered problem in a real world situation. A new mathematical model for this type of the problem is presented that minimizes the waste collection cost and decreases the risk posed to the environment for hazardous wastes transportation simultaneously. According to the NP-hard nature of the problem, a new multi-objective hybrid cultural and genetic algorithm (MOHCG) is proposed to obtain Pareto solutions. A straightforward representation for coding the given model is proposed to help us in reducing the computational time. To validate the proposed algorithm, a number of test problems are conducted and the obtained results are compared with the results of the well-known multi-objective evolutionary algorithm, namely non-dominated sorting genetic algorithm (NSGA-II), with respect to some comparison metrics. Finally, the conclusion is provided.

    Keywords: Waste collection, transportation vehicle routing, Multi-Objective Optimization, Cultural algorithm
  • M. Nayebi, F.Hosseinzadeh Lotfi * Pages 43-66

    The science of Data Envelopment Analysis (DEA) evaluates the effectiveness of decision making units. But, one of the problems of Data Envelopment Analysis (DEA) is that, if the number of units with the same efficiency equal to one was more than one, then we couldn’t select the best between them. It means that, we can’t rank them. Therefore, the need for ranking these units is considered by the managers. Different methods were proposed in this context. Most of these methods are modeled by DEA models. Due to the variety of ranking methods in DEA, this paper will describe ranking methods which are based on super-efficiency. More precisely, we introduced methods that rank using elimination (removing) of decision making units under the evaluation of observations(set). These methods have some advantages and disadvantages such as, model feasibility or infeasibility, stability or instability, being linear or nonlinear, being radial or non-radial, existence or non- existence of bounded optimal solution in objective function, existence or non- existence of multiple optimal solution, non-extreme efficient units ranking, complexity or simplicity of computational processes, that in this paper, Super Efficiency methods are compared with these eight properties.

    Keywords: Data Envelopment Analysis, Ranking Technique, Efficiency, Super Efficiency