Showing 7 results for Scheduling
Gh. Moslehi and H. Ghahar,
Volume 25, Issue 2 (1-2007)
Abstract
This paper deals with resource unconstrained project scheduling problems with the objective of maximizing the net present value (NPV) of project cash flows. Here we present a heuristic algorithm named as differential procedure (Dif_AOA).
In order to evaluate the efficiency of this algorithm, networks with node numbers between 10-1000 and network complexity coefficients between 1.3-6.6 have been generated. We have compared both the total time for solving the problem and NPV of the Dif_AOA with those of the recursive search procedure. Computational results show that the Dif_AOA performs very effectively.
Extensive analysis have been performed to evaluate the node number, complexity network coefficients(CNC), and deadline.
M.r. Amin Naseri, I. Nakhaee, and M. A. Beheshti Nia,
Volume 26, Issue 2 (1-2008)
Abstract
In this paper, the problem of batch scheduling in a flexible flow shop environment is studied. It is assumed that machines in some stages are able to process a number of jobs simultaneously. The applications of this problem can be found in various industries including spring and wire manufacturing and in auto industry. A mixed integer programming formulation of the problem is presented and it is shown that the problem is NP-Hard. Three heuristics will then be developed to solve the problem and a lower bound is also developed for evaluating the performance of the proposed heuristics. Results show that heuristic H3 gives better results compared to the others.
G. Moslehi and M. Mahnam,
Volume 27, Issue 2 (1-2009)
Abstract
While a great portion of the scheduling literature focuses on time-based criteria, the most important goal of management is maximizing the profitability of the firm. In this paper, the net preset value criterion is studied taking account of linear time-dependent cash flows in single machine and flow shop scheduling problems. First, a heuristic method is presented for the single machine scheduling problem with NPV criterion. Second, the permutation flow shop scheduling problem is studied with NPV criterion. An efficient Branch & Bound algorithm is accordingly presented using strong lower and upper bounds and dominace rules which are expanded for this problem. Finally, three heuristic methods are presented and compared to find
appropriate solutions over short periods. By generating random problems of different sizes, it has been shown that the Branch & Bound method is efficient in solving small and medium sized problems, and also that the presented heuristic algorithm is efficient in tackling problems of any size.
H. Zohali, B. Naderi, M. Mohammadi,
Volume 36, Issue 2 (3-2018)
Abstract
This paper addresses the lot sizing and scheduling problem for a number of products in flexible flow shop with identical parallel machines. The production stages are in series, while separated by finite intermediate buffers. The objective is to minimize the sum of setup and inventory holding costs per unit of time. The available mathematical model of this problem in the literature suffers from huge complexity in terms of size and computation. In this paper, a new mixed integer linear program is developed for delay with the huge dimentions of the problem. Also, a new meta heuristic algorithm is developed for the problem. The results of the numerical experiments represent a significant advantage of the proposed model and algorithm compared with the available models and algorithms in the literature.
S. M. Navabi, M. Reisi-Nafchi, Gh. Moslehi,
Volume 38, Issue 2 (2-2020)
Abstract
Nowadays, outpatient providers are struggling to reduce the current costs and improve the service quality. A part of the outpatient service provider is a hemodialysis department with expensive supplies and equipment. Therefore, in the present paper, the scheduling of hemodialysis patients with their preferences has been studied. The aim of scheduling hemodialysis patients in this study is to minimize the normalized weighted sum of deviations from the patients' preferences and the total completion time. It should be noted that the patient's preferences include beds, treatment combination of days and their turn. To solve the problem, two mathematical models have been presented. Performence of the models in solving the real data of the hemodyalisis department of Imam Khomeini Hospital, in Kermanshah, was investigated. The results showed the efficiency of the proposed models in considering the preferences of patients; however, these preferences in the hospital schedule were considered in few cases, as far as it was possible. So, these preferences has no priority in the hospital schedule. In addition to considering the patients’ preferences, the solution of models reduced the total completion time of the pationts treatment. Also, one of the proposed models in this papercould optimally solve the instances three times larger than the hospital cases
N. Fattahi, M. Reisi-Nafchi, G. Moslehi,
Volume 39, Issue 1 (8-2020)
Abstract
Scheduling in production environments is used as a competitive tool to improve efficiency and respond to customer requests. In this paper, a scheduling problem is investigated in a three-stage flexible flowshop environment with the consideration of blocking and batch processing. This problem has been inspired by the charging and packaging line of a large battery manufacturer. In this environment, the first and third stages involve a single processor machine, and the second one consists of m identical parallel batch processing machines. The objective is to minimize the total weighted tardiness of the received orders.Given the lack of consideration of this problem in the literature, first, a mathematical programming model is presented for the problem. Also, due to the NP-hardness of the problem, a variable neighborhood search algorithm and a memetic algorithm are developed to solve it. The computational results show that the variable neighborhood search algorithm can solve instances up to 1200 orders and 15 machines with an average deviation of about 1.9%, relative to the best solution of the two algorithms, and the memetic algorithm can solve instances up to 1200 orders and 15 machines with an average deviation of about 7.8%, as compared e to the best solution of the two algorithms. In general, computational results show the better performance of the variable neighborhood search algorithm in comparison to the memetic algorithm.
S. Moomivand, H. Davari-Ardakani, H. Mosadegh, M. Abouei Ardakan,
Volume 40, Issue 1 (9-2021)
Abstract
In this paper, a multi-mode resource constrained project selection and scheduling problem is investigated considering the reinvestment strategy in a flexible time horizon. Among a set of available projects, a number of projects are selected and scheduled regarding the constraints on renewable resources and precedence relations. The benefits of project portfolio selection and scheduling are compared in both fixed and flexible time horizons. For this purpose, upper and lower tolerance limits are considered for the predetermined time horizon. If the schedule exceeds the time horizon, a penalty cost will be charged. The objective is to determine the optimal time horizon. A mixed-integer linear programming model is proposed for this problem, and solved by GAMS software/CPLEX solver and also a combination of a proposed heuristic algorithm, Genetic Algorithm, and a local search method. Numerical results show that the proposed approach has an acceptable performance in terms of the quality of the solution and the running time. Also, dealing with the problem in a flexible time horizon is more profitable compared to a fixed time horizon.
