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Growing Science » International Journal of Industrial Engineering Computations

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Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach Pages 1-12 Right click to download the paper Download PDF

Authors: Ripon Kumar Chakrabortty, Md. A. Akhtar Hasin

DOI: 10.5267/j.ijiec.2012.09.003

Keywords: Aggregate production planning, Genetic algorithm, Multi-objective optimization

Abstract:
In hierarchical production planning system, Aggregate Production Planning (APP) falls between the broad decisions of long-range planning and the highly specific and detailed short-range planning decisions. This study develops an interactive Multi-Objective Genetic Algorithm (MOGA) approach for solving the multi-product, multi-period aggregate production planning (APP) with forecasted demand, related operating costs, and capacity. The proposed approach attempts to minimize total costs with reference to inventory levels, labor levels, overtime, subcontracting and backordering levels, and labor, machine and warehouse capacity. Here several genetic algorithm parameters are considered for solving NP-hard problem (APP problem) and their relative comparisons are focused to choose the most auspicious combination for solving multiple objective problems. An industrial case demonstrates the feasibility of applying the proposed approach to real APP decision problems. Consequently, the proposed MOGA approach yields an efficient APP compromise solution for large-scale problems.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 4971 | Reviews: 0

 
2.

Network design and operational modelling for construction green supply chain management Pages 13-28 Right click to download the paper Download PDF

Authors: Pengfei Zhou, Dong Chen, Qiuliang Wang

DOI: 10.5267/j.ijiec.2012.11.001

Keywords: Environmental Performance, Green Supply Chain Management, Mathematical Programming, Reverse Logistics

Abstract:
Based on studying organizational structure of Construction Green Supply Chain Management (CGSCM), a mathematical programming model of CGSCM was proposed. The model aimed to maximize the aggregate profits of normalized construction logistics, the reverse logistics and the environmental performance. Numerical experiments show that the proposed approach can improve the aggregate profit effectively. In addition, return ratio, subsidies from governmental organizations, and environmental performance were analyzed for CGSCM performance. Herein, the proper return, subsidy and control strategy could optimize construction green supply chain.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 2983 | Reviews: 0

 
3.

Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems Pages 29-50 Right click to download the paper Download PDF

Authors: R. Venkata Rao, Vivek Patel

DOI: 10.5267/j.ijiec.2012.09.001

Keywords: Number of generations, Population size, Elitism, Teaching-learning-based optimization, Unconstrained optimization problems

Abstract:
Teaching-Learning-based optimization (TLBO) is a recently proposed population based algorithm, which simulates the teaching-learning process of the class room. This algorithm requires only the common control parameters and does not require any algorithm-specific control parameters. In this paper, the effect of elitism on the performance of the TLBO algorithm is investigated while solving unconstrained benchmark problems. The effects of common control parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 76 unconstrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. A statistical test is also performed to investigate the results obtained using different algorithms. The results have proved the effectiveness of the proposed elitist TLBO algorithm.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 4097 | Reviews: 0

 
4.

Optimization of machining parameters of turning operations based on multi performance criteria Pages 51-60 Right click to download the paper Download PDF

Authors: Abhijit Saha, N.K. Mandal

DOI: 10.5267/j.ijiec.2012.11.004

Keywords: Power consumption, Turning, Frequency of tool vibration, Grey relational analysis, Surface roughness

Abstract:
The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA). Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 3247 | Reviews: 0

 
5.

A multi supplier lot sizing strategy using dynamic programming Pages 61-70 Right click to download the paper Download PDF

Authors: Iman Parsa, Mohsen Emadi Khiav, Mohammad Mahdavi Mazdeh, Saharnaz Mehrani

DOI: 10.5267/j.ijiec.2012.11.003

Keywords: Dynamic programming, Lot sizing, Quantity discounts, Supplier selection, Supply chain

Abstract:
In this paper, the problem of lot sizing for the case of a single item is considered along with supplier selection in a two-stage supply chain. The suppliers are able to offer quantity discounts, which can be either all-unit or incremental discount policies. A mathematical modeling formulation for the proposed problem is presented and a dynamic programming methodology is provided to solve it. Computational experiments are performed in order to examine the accuracy and the performance of the proposed method in terms of running time. The preliminary results indicate that the proposed algorithm is capable of providing optimal solutions within low computational times, high accuracy solutions.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 2974 | Reviews: 0

 
6.

Optimization of process parameters for friction Stir welding of dissimilar Aluminum alloys (AA2024 -T6 and AA6351-T6) by using Taguchi method Pages 71-80 Right click to download the paper Download PDF

Authors: P. Murali Krishna, N. Ramanaiah, K. Prasada Roa

DOI: 10.5267/j.ijiec.2012.11.002

Keywords: Friction stir welding, Optimization, Process Parameters, Taguchi

Abstract:
The present study focused on the Taguchi experimental design technique of Friction Stir Welds of dissimilar aluminum alloys (AA2024-T6 and AA6351-T6) for tensile properties. Effect of process parameters, rotational speed, Traverse speed and axial force, on tensile strength was evaluated. Optimized welding conditions for maximize tensile strength were estimated in order to improve the productivity, weld quality. Non-linear regression mathematical model was developed to correlate the process parameters to tensile strength. The results were verified by conducting the confirmation tests at identified optimum conditions.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 4076 | Reviews: 0

 
7.

Three stage supply chain model with two warehouse, imperfect production, variable demand rate and inflation Pages 81-92 Right click to download the paper Download PDF

Authors: S.R. Singh, Vandana Gupta, Preety Gupta

DOI: 10.5267/j.ijiec.2012.10.005

Keywords: Imperfect items, inflation, Partially backlogging, Supply chain model, Two warehouse, Variable demand rate

Abstract:
This study develops an integrated production inventory model from the perspectives of vendor, supplier and buyer. The demand rate is time dependent for the vendor and supplier and buyer assumes the stock dependent demand rate. As per the demand, supplier uses two warehouses (rented and owned) for the storage of excess quantities. Shortages are allowed at the buyer’s part only and the unfulfilled demand is partially backlogged. The effect of imperfect production processes on lot sizing is also considered. This complete model is studied under the effect of inflation. The objective is to minimize the total cost for the system. A solution procedure is developed to find a near optimal solution for the model. A numerical example along with sensitivity analysis is given to illustrate the model.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 3005 | Reviews: 0

 
8.

A location-inventory model for distribution centers in a three-level supply chain under uncertainty Pages 93-110 Right click to download the paper Download PDF

Authors: Sara Gharegozloo Hamedani, M. Saeed Jabalameli, Ali Bozorgi-Amiri

DOI: 10.5267/j.ijiec.2012.10.004

Keywords: Multi-objective particle swarm Optimization, Facility location, Location-inventory, Supply chain network design, Uncertainty

Abstract:
We study a location-inventory problem in a three level supply chain network under uncertainty, which leads to risk. The (r,Q) inventory control policy is applied for this problem. Besides, uncertainty exists in different parameters such as procurement, transportation costs, supply, demand and the capacity of different facilities (due to disaster, man-made events and etc). We present a robust optimization model, which concurrently specifies: locations of distribution centers to be opened, inventory control parameters (r,Q), and allocation of supply chain components. The model is formulated as a multi-objective mixed-integer nonlinear programming in order to minimize the expected total cost of such a supply chain network comprising location, procurement, transportation, holding, ordering, and shortage costs. Moreover, we develop an effective solution approach on the basis of multi-objective particle swarm optimization for solving the proposed model. Eventually, computational results of different examples of the problem and sensitivity analysis are exhibited to show the model and algorithm & apos; s feasibility and efficiency.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 3911 | Reviews: 0

 
9.

Designing reliable supply chain network with disruption risk Pages 111-126 Right click to download the paper Download PDF

Authors: Fateme Bozorgi Atoei, Ebrahim Teimory, Ali Bozorgi Amiri

DOI: 10.5267/j.ijiec.2012.10.003

Keywords: Reliability, Disruption risk, Network design, Supply chain

Abstract:
Although supply chains disruptions rarely occur, their negative effects are prolonged and severe. In this paper, we propose a reliable capacitated supply chain network design (RSCND) model by considering random disruptions in both distribution centers and suppliers. The proposed model determines the optimal location of distribution centers (DC) with the highest reliability, the best plan to assign customers to opened DCs and assigns opened DCs to suitable suppliers with lowest transportation cost. In this study, random disruption occurs at the location, capacity of the distribution centers (DCs) and suppliers. It is assumed that a disrupted DC and a disrupted supplier may lose a portion of their capacities, and the rest of the disrupted DC & apos; s demand can be supplied by other DCs. In addition, we consider shortage in DCs, which can occur in either normal or disruption conditions and DCs, can support each other in such circumstances. Unlike other studies in the extent of literature, we use new approach to model the reliability of DCs; we consider a range of reliability instead of using binary variables. In order to solve the proposed model for real-world instances, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied. Preliminary results of testing the proposed model of this paper on several problems with different sizes provide seem to be promising.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 3968 | Reviews: 0

 
10.

Differential evolution algorithm for multi-commodity and multi-level of service hub covering location problem Pages 127-138 Right click to download the paper Download PDF

Authors: M. EghbaliZarch, M. Abedzadeh, M. Setak

DOI: 10.5267/j.ijiec.2012.10.001

Keywords: Multi-commodity, Differential evolution algorithm, Hub covering location, Lower and upper bounds, Multi-level of service, Response surface methodology

Abstract:
The hub location problem involves a network of origins and destinations over which transportation takes place. There are many studies associated with finding the location of hub nodes and the allocation of demand nodes to these located hub nodes to transfer the only one kind of commodity under one level of service. However, in this study, carrying different commodity types from origin to destination under various levels of services (e.g. price, punctuality, reliability or transit time) is studied. Quality of services experienced by users such as speed, convenience, comfort and security of transportation facilities and services is considered as the level of service. In each system, different kinds of commodities with various levels of services can be transmitted. The appropriate level of service that a commodity can be transmitted through is chosen by customer preferences and the specification of the commodity. So, a mixed integer programming formulation for single allocation hub covering location problem, which is based on the idea of transferring multi commodity flows under multi levels of service is presented. These two are applied concepts, multi-commodity and multi-level of service, which make the model & apos; s assumptions closer to the real world problems. In addition, a differential evolution algorithm is designed to find near-optimal solutions. The obtained solutions using differential evolution (DE) algorithm (upper bound), where its parameters are tuned by response surface methodology, are compared with exact solutions and computed lower bounds by linear relaxation technique to prove the efficiency of proposed DE algorithm.
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Journal: IJIEC | Year: 2013 | Volume: 4 | Issue: 1 | Views: 14429 | Reviews: 0

 
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