فهرست مطالب
 Volume:25 Issue: 4, 2018
 Transactions on Industrial Engineering (E)
 تاریخ انتشار: 1397/05/05
 تعداد عناوین: 10


Pages 22332253The production scheduling problem in hybrid flow shops is a complex combinatorial optimization problem observed in many realworld applications. The standard hybrid flow shop problem involves often unrealistic assumptions. In order to address the realistic assumptions, four additional traits were added to the proposed problem. These include reentrant line, setup times, positiondependent learning effects, and the consideration of maximum completion time together with total tardiness as objective function. Since the proposed problem is nondeterministic polynomialtime (NP)hard, a metaheuristic algorithm is proposed as the solution procedure. The solution procedure is categorized as an a priori approach. To show the efficiency and effectiveness of the proposed algorithm, computational experiments were done on various test problems. Computational results show that the proposed algorithm can obtain an effective and appropriate solution quality for our investigated problemKeywords: Re, entrant hybrid flow shop, Setup times, Learning effect, Multi, objective problems, A priori approach

Pages 22542266Pricing and advertising is one of the most important decisions in each supply chain especially in the competitive environment. In the previous studies, this is as a centralized decision. However, if each channel member makes its decision independently, the utility of all members is optimized. In such decentralized situations, the channel members may have different market power that they influence on the other members decisions. These issues can modeled through leaderfollower Stackelberg game or bilevel programming. This study investigates coordination of pricing and cooperative advertising in a twostage supply chain consisting of one dominantretailer and multiple competitive manufactures which produce several perishable and substitutable products. This paper aims to determine pricing and cooperative advertising decisions expenditure as well as the amount of manufacturers production or retailers purchase such that utility of all members is met. Hence, the problem is modeled as a multifollower bilevel programming problem. Since it is proved that the model is NPhard, the proposed model is solved through simulated annealing. A numerical example is used to show the impact of demands variations on the members decisions.Keywords: Bi, level Programming, Pricing, Dominant, retailer supply chain, Substitutable, perishable products, cooperative advertising, Simulated annealing

Pages 22672281In some processes, quality of a product should be characterized by functional relationships between response variables and a signal factor. Hence the traditional methods cannot be used to find the optimum solution. In this paper, we propose a method which considers two different dispersion effects, i.e. in domain and between replicates variations in the functional responses. Besides, we propose an integral based measure to find the deviation from target function. A probabilistic method is applied to consider the correlation structure of functional responses. Three numerical examples and a real case from literature are studied to show the efficiency of the proposed methodKeywords: Multiple Responses Optimization, Functional Responses, Design of Experiments, Polynomial integral

Pages 22822296Crossdocking is one of the supply chain strategies that can reduce transportation and inventory costs. Many studies are conducted the problem of crossdocking by considering various characteristics of crossdocks. In this paper, a queuing model is proposed in order to optimize the number of outbound doors based on minimizing the total costs including the costs of adding a new outbound door and the expected waiting time of customers. The total number of trucks arriving for service is constant. Trucks arrive to outbound doors of the crossdock within a specified time window. Arrival times of trucks follow a beta distribution and customers to be served based on first in first out policy (FIFO). Since, the total number of customers as well as the time of arrivals are finite, the steady state distribution for the long run of the system is inapplicable. Instead, based on conditional joint probabilities, order statistics along with the Bayes theorem we calculate the total expected waiting time.Keywords: crossdock, queuing system, non, stationary, order statistics, conditional probability

Pages 22972311This paper proposes an innovative robustfuzzy method for multiobjective, multiperiod supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and specially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which can be applicable to multiple uncertainties conditions. Thus, in our approach the halflength of these intervals is also represented by fuzzy membership function. We develop a model and a solution approach to select suppliers by considering risk. The proposed method is applied to a real case of supplier selection in automobile industry under uncertainty and ambiguity conditions. To verify the proposed model, we evaluated the results by simulation technique and compared values of objective function under different scenarios.Keywords: Supplier selection, uncertainty, Robust Optimization, Fuzzy programming, Robust, fuzzy model, Auto industry

Pages 23122330In the event of natural disasters, relief distribution is the most challenging problem of emergency transportation. What is important in response to disaster is victims relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. So, this paper considers a problem using a threestage approach. In the first stage, preprocessing of model inputs is done through an artificial neural fuzzy inference system (ANFIS) followed by investigating the safest route for each cluster using of decisionmaking techniques and graph theory. In the second stage, a heterogeneous multidepots multimode vehicle routing problem is formulated for minimizing the transportation time and maximize the reliability. Finally, since the routing problem is NPhard, two multiobjective metaheuristic algorithms, namely nondominated sorting genetic algorithm (NSGAII) and multiobjective firefly algorithm (MOFA), are proposed to obtain the optimal solution and compared their performance through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions in comparison to NSGAII and performs well in terms of accuracy and solution time.Keywords: Disaster, Relief distribution, Vehicle routing problem, clustering, Reliability, multi, objective meta, heuristics

Pages 23312346This study considers a multiproduct multimachine economic production quantity inventory problem in an imperfect production system that produces two types of defective items: items that require rework and scrapped items. The shortage is allowed and fully backordered. The scrapped items are disposed with a disposal cost and the rework is done at the end of the normal production period. Moreover, a potential set of available machines for utilization is considered such that each has a specific production rate per item. Each machine has its own utilization cost, setup time and production rate per item. The considered constraints are initial capital to utilize machines and production floor space. The proposed inventory model is a mixed integer nonlinear programing mathematical model. The problem is solved using a bilevel approach, first, the set of machines to be utilized and the production allocation of items on each machine are obtained thru a genetic algorithm. Then, using the convexity attribute of the second level problem the optimum cycle length per machine is determined. The proposed hybrid genetic algorithm outperformed conventional genetic algorithm and a GAMS solver, considering solution quality and solving time. Finally, a sensitivity analysis is also given.Keywords: EPQ, defective item, MINLP, shortage, Hybrid algorithm

Pages 23472360This paper proposes an integrated twostage model, which consists of one vendor and one buyer for two complementary products. The vendor produces two types of products and delivers them to the buyer in distinct batches. Buyer stocks items in the warehouse and on the shelf. The demand for each product is sensitive to stock levels of both products. A vendor managed inventory with consignment stock policy is considered. The number of shipments and replenishment lot sizes are jointly determined as decision variables in such a way that total profit is maximized. The numerical study shows that as complementary rate increases, the quantity of transfers and demand of both products increase. Hence, ignoring the complementation between products leads to some customers lost.Keywords: supply chain coordination, Inventory control, Complementary products, Stock dependent demand, Consignment, vendor managed inventory

Pages 23612372We proposed efficient families of ratiotype estimators to estimate finite population mean using known correlation coefficient between study variable and auxiliary variable by adopting Singh and Tailor [Singh, H. P., and Tailor, R. Use of known correlation coefficient in estimating the finite population means, Statistics in Transition, 6(4), pp. 555560 (2003)] estimator and Kadilar and Cingi [Kadilar, C., and Cingi, H. An improvement in estimating the population mean by using the correlation coefficient, Hacettepe Journal of Mathematics and Statistics, 35(1) pp. 103109. (2006a)] class of estimators in simple random sampling without replacement. The newly proposed estimators behave efficiently as compared to the common unbiased estimator, traditional ratio estimator and the other competing estimators. Bias, mean squared error and minimum mean squared error of the proposed ratiotype estimators are derived. Moreover, theoretically findings are proved with cooperation of two real data sets.Keywords: Auxiliary variable, Bias, Correlation Coefficient, Efficiency, Mean squared error, Ratio, type estimators

Pages 23732388Set pair analysis (SPA) is an updated theory for dealing with the uncertainty, which overlaps the other theories of uncertainty such as probability, vague, fuzzy and intuitionistic fuzzy set (IFS). Considering the fact that the correlation coecient plays an important role during the decisionmaking process, in this paper, after pointing out the weakness of the existing correlation coecients between the IFSs, we propose a novel correlation coecient and weighted correlation coecients formulation to measure the relative strength of the di erent IFSs. For it, rstly corresponding to each intuitionistic fuzzy number, the connection number of the SPA theory has been formulated in the form of the degree of identity, discrepancy and contrary and then based on its, a novel correlation coecient measures have been de ned. Pairs of identity, discrepancy and contrary of the connection number have been taken as a vector representation during the formulation. Lastly, a decisionmaking approach based on the proposed measures has been presented which has been illustrated by two numerical examples in pattern recognition and medical diagnosis.Keywords: Set pair analysis, Connection number, Intuitionistic fuzzy set, Pattern recognition, Medical diagnosis, decision making