International Journal of Industrial Engineering: Theory, Applications and Practice
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HYBRID MODEL TO DESIGN AN AGRO-FOOD DISTRIBUTION NETWORK CONSIDERING THE QUALITY OF THE FOOD
No full textIn the agro-food supply chain, client’s satisfaction is mainly reflected in food freshness in such a way that quality has a direct relation with the selling price. This research work suggests a hybrid model for the design of a food distribution network that maximizes the farmers’ profits depending on the delivered quality by using a mixed integer linear programming model (MILP) and a discrete-event simulation model under certain stochastic parameters. The problem involves only one product (prickly pear), 93 farmers, 53 distribution centers and 27 markets. The results determined that the available offer (amount) of prickly pear of the 93 farmers must be sent to 29 distribution centers to satisfy the demand of the market, the delivered quality of the fruit at the market is in an interval from 84% and 94%
Determining Number of Withdrawal Kanban Using Bi-Level Optimization and Simulation Approaches
No full textWithdrawal Kanban system, by capability of data transferring in supply chain reduces different types of the wastes such as inventories level and unnecessary movements. To achieve the aims of lean production, the parameters of the Kanban system such as the number of Kanban should be determined accurately. The number of Kanban problem is a bi-level optimization problem, because manufacturer and suppliers have different and in competition objectives and decision variables. In this paper, the objectives and constraints of withdrawal Kanban problem has been determined based on a case study in automobile industry supply chain. A mathematical bi-level optimization model with non-linear objectives has been developed and A Genetic Algorithm model for solving is proposed. Also, a simulation model is developed to check the possibility, feasibility and validity of solutions. The simulation studies show one of the feasible solutions can reduce up to 16 percent the transportation costs
A Bayesian Approach for Predicting Functional Reliability of One-Shot Devices
No full textAccelerated life tests (ALTs) have been used to assess reliability of one-shot devices in a short time. Due to destructive characteristics of one-shot devices, lifetime data of the devices is incomplete and enough number of failures or even no failures may be not secured in ALT. In such situations, Baysian methods incorporating prior information into the parameters provides useful inference on the reliability of one-shot devices. In this paper, we propose a modeling approach to predict functional reliability of pin pullers as a kind of one-shot devices, mainly in a Bayesian framework. We introduce three different priors to the parameters of the Weibull distribution or reliability function. Sress-strength relationships of key components in pin pullers are employed to the scale and shape parameters via three prior densities. The proposed methods are illustrated with a variety of simulation studies. The simulation works are performed using the Gibbs sampling technique to generate MCMC samples to obtain Bayesian estimates of the Weibull parameters. The Bayesian estimates from the three priors tend to approach to true parameter values as sample size increases
DEVELOPING AN ENHANCED PORTFOLIO TRADING SYSTEM USING K-MEANS AND GENETIC ALGORITHMS
No full textThe objective of this study is to enhance the ability of an index fund strategy using k-means clustering and genetic algorithms. This study proposes a novel enhanced portfolio mechanism consisting of two phases. In the first phase, a subset of all the index shares is selected using k-means clustering based on investor information. In the second phase, a genetic algorithm is employed to search for the optimal stock weights in the selected clusters. In order to identify the usefulness of the proposed model, this study is compared with the conventional approach. For measuring trading performance, the tracking error, which a measure of how closely a portfolio follows the index as a benchmark, is evaluated. Furthermore, the information ratio is used to compare the performance of the proposed model in terms of the risk-adjusted return. An empirical study of the proposed model is simulated in the Korea stock exchange market
DESIGNING AN OPTIMAL INVENTORY REPLENISHMENT STRATEGY IN A COMBINED MTS-MTO SUPPLY CHAIN
No full textWe consider a combined MTS-MTO supply chain in which an MTO manufacturer replenishes component inventory from contract suppliers on a MTS basis. Two types of component replenishment strategies are evaluated; multiple suppliers with a fixed order quantity and a single supplier with volume flexibility. For each strategy, we determine an optimal order size, when to place an order for inventory replenishment and an optimal number of suppliers when there are multiple suppliers. This paper formulates the problem as a discrete Markov Decision Process and proposes a solution procedure based on the value iteration algorithm for each strategy. Extensive numerical analysis provides interesting findings. First, the use of an optimal replenishment strategy is dependent not only on the lead-time but also on the traffic intensity and production rate at the MTO manufacturer. Second, the multiple-supplier strategy is likely to outperform the single supplier strategy under heavy traffic intensity, high degree of lead time uncertainty and small size of maximum allowable backorders. Third, the optimal policy for ordering inventory is of the control limit type. Furthermore, the multiple-supplier strategy generally has a lower reorder point than that of the single supplier strategy
Comparative Study of Adaptive Multivariate EWMA Control Charts
No full textThe purpose of this study is to compare the optimal statistical performances among the adaptive multivariate exponentially weighted moving average (MEWMA) control charts, i.e. variable sample sizes (VSS) chart, variable sampling intervals (VSI) chart, and variable sample sizes and sampling intervals (VSSI) chart. It is shown that the optimal VSI and VSSI MEWMA charts are more efficient than the optimal VSS MEWMA chart for detecting shifts in the process mean vector. In addition, it is also shown that all the optimal adaptive MEWMA charts perform better than the corresponding fixed sampling rate (FSR) MEWMA chart for detecting shifts in the process mean vector
A model proposal for ERP system selection in automotive industry
No full textERP turned out to be one of the most valuable tools since it is a strong means to integrate the functions both within a company and among the companies within a supply chain. This study aims to propose a comprehensive model to evaluate alternative ERP packages and select the best one. The hierarchical model proposed in this study is applicable in any industry with minor modifications. However, considering the importance of automotive industry both for global and national economies, harsh competition, and many industry specific requirements, a dedicated full model is proposed. This industry specific nature together with the comprehensive model constitutes the major originality of the study. Fuzzy AHP is used to calculate the weights of criteria and sub-criteria within the model. Then, to illustrate the application of the model, fuzzy TOPSIS is utilized in a numerical example for ranking three alternative ERP systems
RESPONSE TO DEMAND UNCERTAINTY OF SUPPLY CHAINS: A VALUE-FOCUSED APPROACH WITH AHP AND TOPSIS
No full textThis paper aims to develop a management framework that can assist managers identify the risks in their supply chain, and assess potential solutions for these risks. Two multi-attributed decision analysis tools, namely, analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) are utilized. The framework proposed is implemented in one electronics company in Taiwan, with three plants in mainland China. With this framework, the case company identifies four sorts of risks in their supply chain, e.g. production, labor, material, and fulfilment, and further determines which plant is most appropriate for order allocation. Further, this framework assists the company to reveal the weakest functions of each factory. As such it facilitates the company in making decisions of the resource allocation among the three plants. It thus contributes to supply chain managers in evaluating the risk factors of each manufacturing site and developing appropriate strategy
A HIERARCHICAL BAYESIAN NETWORK TO COMPARE MAINTENANCE STRATEGIES BASED ON COST AND RELIABILITY: A CASE OF ONSHORE WIND TURBINES
No full textToday we encounter systems which consist of several vital components interacting with environment, and organizational factors. This necessitates an approach which is enabled to consider various aspects of systems and underlying interactions. To clearly illustrate this concept, we develop a Bayesian network (BN). The model enables decision makers to trace the impacts of applying different maintenance strategies on subsystems reliabilities. The model is applied to evaluate various maintenance strategies impacts on the reliability of a wind turbine. A low reliable wind turbine suffers from high turbine failure rate leading to a high Cost of Energy (CoE) due to high Operating and Maintenance (O&M) costs, as well as lost revenue from electricity sales. The most effective means of minimizing O&M costs is to improve reliability. This paper examines the consequences of applying maintenance strategies on O&M costs. Applying this integrated approach in reliability analysis can contribute to costs and revenues trade-off. 
LOT SIZING PROBLEM FOR FAST MOVING PERISHABLE PRODUCT: MODELING AND SOLUTION APPROACH
No full textIn this paper, the integrated lot sizing problem for perishable products is investigated. The problem is modeled as a single vendor multiple buyer system. A variant of the truckload discount scheme is applied and the proposed model is formulated as a mixed integer program (MIP). The traditional warehouses are replaced by ‘cross-docks’ and situations in which, cross-docking would be more beneficial are highlighted. The problem of fleet selection is also addressed and various strategies to minimize the vendor cost are discussed for centralized and decentralized supply chains. Sensitivity analysis performed on the input parameters underscores the significant impact of economies of scale in transportation on the total supply chain cost. Analysis of lead time-cost tradeoff reveals that alternate modes of transportation could be explored which reduces significantly the lead time of transportation, consequently reducing the total supply chain cost. The robust nature of the model formulation extends its application to scenarios with uncertain demands