Showing 7 results for Mathematical Model
R. Tavakkoli-Moghaddam, M. Aryanezhad, H. Kazemipoor , A. Salehipour ,
Volume 19, Issue 1 (3-2008)
Abstract
Abstract : A tandem automated guided vehicle (AGV) system deals with grouping workstations into some non-overlapping zones , and assigning exactly one AGV to each zone. This paper presents a new non-linear integer mathematical model to group n machines into N loops that minimizes both inter and intra-loop flows simultaneously. Due to computational difficulties of exact methods in solving our proposed model, a threshold accepting (TA) algorithm is proposed. To show its efficiency, a number of instances generated randomly are solved by this proposed TA and then compared with the LINGO solver package employing the branch-and-bound (B/B) method. The related computational results show that our proposed TA dominates the exact algorithm when the size of instances grows.
I. Mahdavi, M. M. Paydar, M. Solimanpur , M. Saidi-Mehrabad,
Volume 21, Issue 2 (5-2010)
Abstract
This paper deals with the cellular manufacturing system (CMS) that is based on group technology concepts. CMS is defined as identifying the similar parts that are processed on the same machines and then grouping them as a cell. The most proposed models for solving CMS are focused on cell formation problem while machine layout is considered in few papers. This paper addresses a mathematical model for the joint problem of the cell formation problem and the machine layout. The objective is to minimize the total cost of inter-cell and intra-cell (forward and backward) movements and the investment cost of machines. This model has also considered the minimum utilization level of each cell to achieve the higher performance of cell utilization. Two examples from the literature are solved by the LINGO Software to validate and verify the proposed model.
Ashwin S. Chatpalliwar, Vishwas S. Deshpande, Jayant P. Modak, Nileshsingh V. Thakur,
Volume 24, Issue 3 (9-2013)
Abstract
This paper mainly focuses the study and analysis of the existing contributions related to the Biodiesel production. It, firstly, discuss the key issues related contributions which include chemical process, reactor designing, plantation, blending and applications. Next, it summarizes the analysis of the other prominent contributions related to process model, design, production, cost, optimization, feasibility, safety, effects, challenges and future of the Biodiesel. It also presents the discussion on the open issues in Biodiesel. Secondly, an approach is suggested for the design of the Biodiesel manufacturing plant in view of cost and capacity. The suggested approach is based on the mathematical model. This paper provides the brief study of Biodiesel production and plant design and it can be helpful to the beginners in the domain of renewable energy research.
Esmaeil Mehdizadeh, Amir Fatehi-Kivi,
Volume 28, Issue 1 (3-2017)
Abstract
In this paper, we propose a vibration damping optimization algorithm to solve a fuzzy mathematical model for the single-item capacitated lot-sizing problem. At first, a fuzzy mathematical model for the single-item capacitated lot-sizing problem is presented. The possibility approach is chosen to convert the fuzzy mathematical model to crisp mathematical model. The obtained crisp model is in the form of mixed integer linear programming (MILP) which can be solved by existing solver in crisp environment to find optimal solution. Due to the complexity and NP-hardness of the problem, a vibration damping optimization (VDO) is used to solve the model for large-scale problems. To verify the performance of the proposed algorithm, we computationally compared the results obtained by the VDO algorithm with the results of the branch-and-bound method and two other well-known meta-heuristic algorithms namely simulated annealing (SA) and genetic algorithm (GA). Additionally, Taguchi method is used to calibrate the parameters of the meta-heuristic algorithms. Computational results on a set of randomly generated instances show that the VDO algorithm compared with the other algorithms can obtain appropriate solutions.
Elham Moazzam Jazi, Hadi Abdollahzadeh Sangroudi,
Volume 31, Issue 1 (3-2020)
Abstract
Biofuels production systems are identified as a potential solution in responding to the ever-increasing energy consumption demand. The complexity of conversion process and supply chain of these systems, however, can make the commercialization of biofuels less attractive, so designing and management of an efficient biofuel supply chain network can resolve this issue. Hence, this paper proposes a multi-period hybrid generation biomass-to-biofuel supply chain considering environmental, economic and technology considerations. The objective is to maximize the total profit that biofuel producers can make with practical constraints including the biomass supply, the capacity of facilities, storage, Greenhouse Gas (GHG) emissions and transportation with limited capacity. To highlight the applicability of the proposed model, it is applied to a biomass-derived liquid fuel supply system in the southern region of Iran. In the case study, wheat and wheat stem are simultaneously considered as the first- and second-generation of feedstocks for biodiesel production. Sensitivity analyses show that available biomasses can have a significant impact on the profitability of this supply chain. The obtained results demonstrate the efficiency and performance of the proposed model in biodiesel supply chain design.
Sofia Kassami, Abdelah Zamma, Souad Ben Souda,
Volume 33, Issue 3 (9-2022)
Abstract
Modeling supply chain planning problems is considered one of the most critical planning issues in Supply Chain Management (SCM). Nowadays, decisions making must be sufficiently sustainable to operate appropriately in a complex and uncertain environment of the market for many years to beyond the next decade. Therefore, making these decisions in the presence of uncertainty is a critical issue,as highlighted in a large number of relevant publications over the past two decades.The purpose of this investigation is to model a multilevel supply chain problem and determine the constraints that prevent the flow from performing properly, subject to various sources and types of uncertainty that characterize the flow. Therefore, it attempts to establish a generic model that relies on the stochastic approach. Several studies have been conducted on uncertainty in order to propose an optimal solution to this type of problem. Thus, in this study, we will use the method of "Mixed integer optimization program" which is the basis of the algorithm that will be employed. This inaccuracy of the supply chain is handled by the fuzzy sets. In this paper, we intend to provide a new model for determining optimal planning of tactical and strategical decision-making levels, by building a conceptual model. Therefore, it enables us to model the mathematical programming problem. We investigate in this attempt, attention to solving the mathematical model. So in the resolution we are going through the algorithm in machine learning, therefore providing as in the end an optimal solution for the planning of production.
Yuvaraj M, Jothi Basu,
Volume 35, Issue 3 (9-2024)
Abstract
Refrigerated trucks in the cold chain enhance the shelf-life of food. In the fruit supply chain (FSC), if each different fruit necessitates its dedicated fleet of refrigerated vehicles, the total cost of the supply chain would increase. On the other hand, if there are several fruits in a single compartment, the quality and freshness of the fruits will be impacted since each fruit requires a different operating temperature. Therefore, partitions are necessary within the container. While the use of cold chain infrastructure will result in a reduction in food loss and an enhancement in food security, it will also incur an increase in the overall cost of the supply chain. Therefore, this paper aims to create a mixed integer non-linear programming (MINLP) mathematical model considering multi-compartment reefer trucks (MCRTs) to minimize the total cost in the FSC. To assess the efficiency of the model, a case study is carried out in India, and the formulated mathematical model is solved using a heuristic approach. The findings indicate that utilizing MCRTs leads to a reduction in the number of vehicles required and a drop in total supply chain cost. Three-compartment reefer trucks offer a more significant cost-saving advantage in the FSC compared to two-compartment reefer trucks. Furthermore, it is noted that operating three distribution centers (DCs) results in a reduction in the overall cost. The decrease in total supply chain costs enhances the affordability of fruits for low-income populations and contributes to the enhancement of food security. In addition to cost reduction, implementing MCRT has also beneficial environmental impacts such as decreased emissions due to a decrease in the number of trucks utilized and reduced food waste.
