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Inventory control with deteriorating items: A state-of-the-art literature review
, Pages: 179-198 Narges Khanlarzade, Babak Yousefi Yegane, Isa Nakhai Kamalabadi and Hiwa Farughi PDF (256K) |
Abstract: The present study reviews different studies on inventory control of deteriorating items in chain supply published over the period 1963- 2013. The study investigates supply chain of the items in terms of various perspectives. Finally, the summary of the studies is shown in two tables for one-echelon and multi-echelon supply chain including the main information and assumptions of each paper. In the mentioned tables, the papers were classified in terms of the type of demand rate, deterioration rate, solution procedure and findings. It can be said that no analysis on the results was done in the present study and it can be only used as a good reference in the study field for other researchers. DOI: 10.5267/j.ijiec.2013.11.003 Keywords: One-echelon supply chain; Multi-echelon supply chain; Deteriorating items; Inventory control |
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2. |
A supplement to an EOQ model with imperfect quality items, inspection errors, shortage backordering, and sales return
, Pages: 199-210 Jia-Tzer Hsu and Lie-Fern Hsu PDF (256K) |
Abstract: Hsu and Hsu (2013a) established a closed-form solution for an EOQ model with imperfect quality items, inspection errors, shortage backordering, and sales returns, where the customers who return the defective items will receive full price refunds; i.e., the returned items are not replaced with good items. In this note, we extend Hsu and Hsu's (2013a) work to consider the case that returned items are replaced with good items. A closed-form solution is developed for the optimal order size and the maximum shortage level. Numerical examples are provided to show the differences in the optimal solutions when returned items are replaced, and when they are not. DOI: 10.5267/j.ijiec.2014.2.001 Keywords: EOQ; Imperfect quality; Misclassification errors; Inventory backordering |
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3. |
Modified economic order quantity (EOQ) model for items with imperfect quality: Game-theoretical approaches
, Pages: 211-222 Milad Elyasi, Farid Khoshalhan and Mohammad Khanmirzaee PDF (256K) |
Abstract: In the recent decade, studying the economic order quantity (EOQ) models with imperfect quality has appealed to many researchers. Only few papers are published discussing EOQ models with imperfect items in a supply chain. In this paper, a two-echelon decentralized supply chain consisting of a manufacture and a supplier that both face just in time (JIT) inventory problem is considered. It is sought to find the optimal number of the shipments and the quantity of each shipment in a way that minimizes the both manufacturer’s and the supplier’s cost functions. To the authors’ best knowledge, this is the first paper that deals with imperfect items in a decentralized supply chain. Thereby, three different game theoretical solution approaches consisting of two non-cooperative games and a cooperative game are proposed. Comparing the results of three different scenarios with those of the centralized model, the conclusions are drawn to obtain the best approach. DOI: 10.5267/j.ijiec.2014.1.003 Keywords: Inventory management; Economic order quantity; Game theory; Non-cooperative games Cooperative games |
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4. |
Optimization of machining processes using pattern search algorithm
, Pages: 223-234 Miloš Madić and Miroslav Radovanović PDF (256K) |
Abstract: Optimization of machining processes not only increases machining efficiency and economics, but also the end product quality. In recent years, among the traditional optimization methods, stochastic direct search optimization methods such as meta-heuristic algorithms are being increasingly applied for solving machining optimization problems. Their ability to deal with complex, multi-dimensional and ill-behaved optimization problems made them the preferred optimization tool by most researchers and practitioners. This paper introduces the use of pattern search (PS) algorithm, as a deterministic direct search optimization method, for solving machining optimization problems. To analyze the applicability and performance of the PS algorithm, six case studies of machining optimization problems, both single and multi-objective, were considered. The PS algorithm was employed to determine optimal combinations of machining parameters for different machining processes such as abrasive waterjet machining, turning, turn-milling, drilling, electrical discharge machining and wire electrical discharge machining. In each case study the optimization solutions obtained by the PS algorithm were compared with the optimization solutions that had been determined by past researchers using meta-heuristic algorithms. Analysis of obtained optimization results indicates that the PS algorithm is very applicable for solving machining optimization problems showing good competitive potential against stochastic direct search methods such as meta-heuristic algorithms. Specific features and merits of the PS algorithm were also discussed. DOI: 10.5267/j.ijiec.2014.1.002 Keywords: Machining; Optimization; Pattern search algorithm |
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5. |
Periodic inventory model with controllable lead time where backorder rate depends on protection interval
, Pages: 235-248 Chandra K Jaggi, Haider Ali and Neetu Arneja PDF (256K) |
Abstract: In this paper, a period review inventory model with controllable lead time has been considered where shortages are partially backlogged. The backorder rate is dependent on the backorder discount and the length of the protection interval, which is sum of the review period and the lead time. Two cases have been discussed for protection interval demand which are (a) Demand distribution is known (Normal Distribution) (b) Demand distribution is unknown (Minimax distribution). Further, algorithms have been developed which jointly optimize the backorder discount, the review period and the lead time for each case. Numerical examples are also presented to illustrate the results. DOI: 10.5267/j.ijiec.2014.1.001 Keywords: Inventory; Periodic review; Crashing cost; Lead-time; Backorder discount, Minimax |
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6. |
Proactive inventory policy intervention to mitigate risk within cooperative supply chains
, Pages: 249-264 Takako Kurano, Kenneth N. McKay and Gary W. Black PDF (256K) |
Abstract: This exploratory paper will investigate the concept of supply chain risk management involving supplier monitoring within a cooperative supply chain. Inventory levels and stockouts are the key metrics. Key to this concept is the assumptions that (1) out-of-control supplier situations are causal triggers for downstream supply chain disruptions, (2) these triggers can potentially be predicted using statistical process monitoring tools, and (3) carrying excess inventory only when needed is preferable as opposed to carrying excess inventory on a continual basis. Simulation experimentation will be used to explore several supplier monitoring strategies based on statistical runs tests, specifically "runs up and down" and/or "runs above and below" tests. The sensitivity of these tests in detecting non-random supplier behavior will be explored and their performance will be investigated relative to stock-outs and inventory levels. Finally, the effects of production capacity and yield rate will be examined. Results indicate out-of-control supplier signals can be detected beforehand and stock-outs can be significantly reduced by dynamically adjusting inventory levels. The largest benefit occurs when both runs tests are used together and when the supplier has sufficient production capacity to respond to downstream demand (i.e., safety stock) increases. When supplier capacity is limited, the highest benefit is achieved when yield rates are high and, thus, yield loss does not increase supplier production requirements beyond its available capacity. DOI: 10.5267/j.ijiec.2013.11.006 Keywords: Supply chain risk management; Dynamic inventory policy; Cooperative supply chain; Simulation and supply chains; Simulation and risk management |
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Modeling the effect of variable work piece hardness on surface roughness in an end milling using multiple regression and adaptive Neuro fuzzy inference system
, Pages: 265-272 Purushottam S. Desale, and Ramchandra S. Jahagirdar PDF (256K) |
Abstract: The aim of this study is to correlate work piece material hardness with surface roughness in prediction studies. The proposed model is for prediction of surface roughness of tool steel materials of hardness 55 HRC to 62 HRC (±2 HRC). The machining experiments are performed under various cutting conditions using work piece of different hardness. The surface roughness of these specimens is measured. The result showed that the influence of work piece material hardness on surface finish is significant for cutting speed and feed in CNC end milling operation. It is also observed that the surface roughness prediction accuracy of Adaptive neuro fuzzy inference system using triangular membership function is better than Gaussian, bell shape membership function and regression analysis. Surface roughness prediction accuracy with material hardness as input parameter is 97.61%. DOI: 10.5267/j.ijiec.2013.11.005 Keywords: End Milling; Tool steel; Surface roughness; Fuzzy inference system; Regression |
8. |
Job shop scheduling with makespan objective: A heuristic approach
, Pages: 273-280 Mohsen Ziaee PDF (256K) |
Abstract: Job shop has been considered as one of the most challenging scheduling problems and there are literally tremendous efforts on reducing the complexity of solution procedure for solving job shop problem. This paper presents a heuristic method to minimize makespan for different jobs in a job shop scheduling. The proposed model is based on a constructive procedure to obtain good quality schedules, very quickly. The performance of the proposed model of this paper is examined on standard benchmarks from the literature in order to evaluate its performance. Computational results show that, despite its simplicity, the proposed heuristic is computationally efficient and practical approach for the problem. DOI: 10.5267/j.ijiec.2013.11.004 Keywords: Scheduling; Job shop; Makespan; Heuristic |
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Scheduling algorithm with controllable train speeds and departure times to decrease the total train tardiness
, Pages: 281-294 Omid Gholami and Yuri N. Sotskov PDF (256K) |
Abstract: The problem of generating a train schedule for a single-track railway system is addressed in this paper. A three stage scheduling is proposed to reduce the total train tardiness. We derived an appropriate job-shop scheduling algorithm called DR-algorithm. In the first stage, by determining appropriate weights of the dispatching rules, a pre-schedule is constructed. In the second stage, on the basis of the pre-schedule, the departure times of the trains are modified to reduce the number of conflicts in using railway sections by different trains. In the third stage, a train speed control helps the scheduler to change the trains’ speeds in order to reduce the train tardiness and to reach other objectives. The factual train schedule is based on the modified train speeds and on the modified departure times of the trains. The experimental running of the DR-algorithm on the benchmark instances showed this algorithm can solve train scheduling problems in a close to optimal way. In particular, the total train tardiness was reduced about 20% due to controlling train speeds and the departure times of the trains. DOI: 10.5267/j.ijiec.2013.11.002 Keywords: Train timetabling; Job-shop scheduling; Makespan; Total tardiness; Dispatching rules |
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10. |
Application of Taguchi and regression analysis on surface roughness in machining hardened AISI D2 steel
, Pages: 295-304 Ashok Kumar Sahoo PDF (256K) |
Abstract: The objective of the study is to assess the performance of multilayer coated carbide insert in the machining of hardened AISI D2 steel (53 HRC) using Taguchi design of experiment. The experiment was designed based on Taguchi L27 orthogonal array to predict surface roughness. The S/N ratio and optimum parametric condition are analysed. The analysis of variance has also been carried out to predict the significant factors affecting surface roughness. Based on Taguchi S/N ratio and ANOVA, feed is the most influencing parameter for surface roughness followed by cutting speed whereas depth of cut has least significant from the experiments. In regression model, the value of R2 being 0.98 indicates that 98 % of the total variations are explained by the model. It indicates that the developed model can be effectively used to predict the surface roughness on the machining of D2 steel with 95% confidence intervals. DOI: 10.5267/j.ijiec.2013.11.001 Keywords: Coated carbide; Taguchi; Surface roughness; ANOVA; Regression |
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11. |
An economic production model for time dependent demand with rework and multiple production setups
, Pages: 305-314 S.R. Singh, Shalini Jain and S. Pareek PDF (256K) |
Abstract: In this paper, we present a model for time dependent demand with multiple productions and rework setups. Production is demand dependent and greater than the demand rate. Production facility produces items in m production setups and one rework setup (m, 1) policy. The major reason of reverse logistic and green supply chain is rework, so it reduces the cost of production and other ecological problems. Most of the researchers developed a rework model without deteriorating items. A numerical example and sensitivity analysis is shown to describe the model. DOI: 10.5267/j.ijiec.2013.10.003 Keywords: Production models; Time dependent demand; Multiple production setups; Rework |
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12. |
Flexible manufacturing system selection using preference ranking methods : A comparative study
, Pages: 315-338 Prasenjit Chatterjee and Shankar Chakraborty PDF (256K) |
Abstract: Flexible manufacturing systems (FMSs) offer opportunities for the manufacturers to improve their technology, competitiveness and profitability through a highly efficient and focused approach to manufacturing effectiveness. Justification, evaluation and selection of FMSs have now been receiving significant attention in the manufacturing environment. Evaluating alternative FMSs in the presence of multiple conflicting criteria and performance measures is often a difficult task for the decision maker. Preference ranking tools are special types of multi-criteria decision-making methods in which the decision maker’s preferences on criteria are aggregated together to arrive at the final evaluation and selection of the alternatives. This paper deals with the application of six most potential preference ranking methods for selecting the best FMS for a given manufacturing organization. It is observed that although the performances of these six methods are almost similar, ORESTE (Organization, Rangement Et Synthese De Donnes Relationnelles) method slightly outperforms the others. These methods use some preference function or utility value or Besson ranking of criteria and alternatives, to indicate how much an alternative is preferred to the others. Most of these methods need quantification of criteria weights or different preference parameters, but ORESTE method, being an ordinal outranking approach, only requires ordinal data and attribute rankings according to their importance. Therefore, it is particularly applicable to those situations where the decision maker is unable to provide crisp evaluation data and attribute weights. DOI: 10.5267/j.ijiec.2013.10.002 Keywords: Flexible manufacturing system; Multi-criteria decision-making; Preference ranking method; Ranking |
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