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.
M. Bashi Varshosaz, B. Naderi, M. Mohammadi,
Volume 37, Issue 1 (9-2018)
Abstract
The purpose of this research is to deal with the problem of two-stage assembly flow shop scheduling. A number of single-item products (identical) each formed of several different parts are ordered. Each part has m operations done at the first stage with m different machines. After manufacturing the parts, they are assembled into a final product with some non-identical machines. The purpose of the problem is to find the optimal sequence of the parts in the manufacturing stage, allocation and the optimal sequence of the products in the assembly stage. A mixed integer linear programming model and two metaheuristic algorithms, which are particle swarm with local search (MPSO) and simulated annealing (SA), are presented to solve this problem. Computational experiments are conducted to evaluate the performance of the proposed model and algorithms. The results show that the MPSO algorithm performs better than the SA one.
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
