International Journal of Supply and Operations ManagementInternational Journal of Supply and Operations Management
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Sat, 24 Feb 2018 04:12:40 +0100FeedCreatorInternational Journal of Supply and Operations Management
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Feed provided by International Journal of Supply and Operations Management. Click to visit.The Comparison of Neural Networks’ Structures for Forecasting
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This paper considers the application of neural networks to demand forecasting in a simple supply chain composed of a single retailer and his supplier with a game theoretic approach. This work analyses the problem from the supplier’s point of view and the employed dataset in our experimentation is provided from a recognized supermarket in Morocco. Various attempts were made in order to optimize the total network error and the findings indicate that different neural net structures can be used to forecast demand such as Adaline, Multi-Layer Perceptron (MLP), or Radial Basis Function (RBF) Network. However, the most adequate one with optimal error is the MLP architecture.Sun, 30 Apr 2017 19:30:00 +0100Optimization of a Multi-product Three-echelon Supply Chain
http://www.ijsom.com/article_2732_0.html
This paper aims at single-objective optimization of multi-product for three-echelon supply chain architecture consisting of production plants, distribution centers (DCs) and customer zones (CZs). The key design decisions considered are: the quantity of products to be shipped from plants to DCs, from DCs to CZs , cycle length, and production quantity so as to minimize the total cost .To optimize the objective, three-echelon network model is mathematically represented considering the associated constraints, production, capacityand shipment costs and solved using genetic algorithm (GA) and Simulated Annealing (SA).Some numerical illustrations are provided at the end to not only show the applicability of the proposed methodology, butalso to select the best method using a t-test along with the simple additive weighting (SAW) method.Tue, 23 Oct 2018 20:30:00 +0100Design of Forward/reverse Logistics with Environmental Consideration
http://www.ijsom.com/article_2726_506.html
Growth of environmental issues has caused to consider various factors that influence on condition of environment. Green supply chain has absorbed care of researchers because of its considerable impacts on environment. In this regard, this study designs the forward/revers logistics network by putting emphasis on environmental aspects in its model such as quantity of CO2 emission. In this logistics network, three objective functions such as minimizing the total cost and quantity of CO2 emission as well as maximizing the satisfaction of customers have been considered, simultaneously. Because of considering of three objective functions in this model, multi objective optimization methods persuade the researchers to implement them. Non-dominated sorting genetic algorithms (NSGA-ӀӀ) and Multi-objective particle swarm optimization (MOPSO) are proposed to cope with this problem. The results acquired from experiments on several test problems are verified by GAMS software. Finally, the results obtained through experiments on different problems verify the superiority of NSGA-ӀӀ over MOPSO in terms of all comparison metrics.Sun, 30 Apr 2017 19:30:00 +0100A Markov Chain Analysis of the Effectiveness of Kanban Card with Dynamic Information
http://www.ijsom.com/article_2733_0.html
The pull system produces products based on customer demands. Each station is isolated until a customer order is placed; then a signal or Kanban is sent from downstream station to upstream station and continues until the first station. Most of the papers studied pull system in deterministic environment while many real production lines are subjected to different types of uncertainties. The objective of this paper is to apply a dynamic Kanban system that changes the information on the Kanban cards based on the remained inventory in the buffer. The proposed approach uses a Markov chain analysis to compare effectiveness of the Kanban card with dynamic information with the Kanban card with static information. In this paper the production line of two work stations and two inventory buffer is modeled. Throughput, shortage, work-in-process and cycle time are the model measurement parameters and the results show the advantages of the proposed approach.Tue, 20 Feb 2018 20:30:00 +0100Modeling the Multi-period and Multi-product Closed-loop Supply Chain Network Design Problem ...
http://www.ijsom.com/article_2727_506.html
The importance of remanufacturing used products into new ones has been widely recognized in the literature and in practice. This is due to both of economic opportunities and environmental aspects. This paper aims to design a new integrated multi-period & multi-product closed-loop supply chain network considering reused cost and capacity constraints for all stages. In this problem the stages of supplier, assembler, retailer, customer, collection center, refurbishing center, and disassembler is regarded consequently. The considered objective function is total cost factors that consists of 7 components: costs of associated with locating the plants and retailers, purchasing, transportation, collection of used products from customers, disposal for subassemblies, refurbishing, and finally refund to customers. First, parameters and decision variables of this problem are defined, then a mixed integer linear programming mathematical model is presented. The proposed mathematical model is run applying the GAMS software. Two real examples (shed light, and power-outlet) are considered to solve using the proposed mathematical model. These two examples were obtained based on data in two new references. Since this problem is known as NP-Hard, the model is run just for small-sized problem consists of four suppliers, two disassemblers, two retailers, and two periods. The results are analysed and some sensitivity analysis have been done for the effective factors. These result show that, the demand has a less effect on total cost. But Purchasing/refurbishing cost ratio has a high effect on the objective function. Finally, the capacity of collection and refurbishing centers has a high effect in primary changes and this effect gradually reduced. So having the proper capacity for collection and refurbishing centers and also creating balance between different stages can reduce overall cost.Sun, 30 Apr 2017 19:30:00 +0100Price discount determination in pricing and inventory control of perishable good with time and ...
http://www.ijsom.com/article_2734_0.html
Determining appropriate inventory control policies and product price are important aspects in the competitive markets of perishable products. Customers’ willing to pay for perishable product is declining when approaching to the end of product’s expiry date. In this paper, we consider price discount in pricing model as an alternative approach to influence on consumers’ purchase decision. The model determines the optimal values of selling price, discount time and replenishment schedule simultaneously such that the total profit is maximized. However, because of demand increase during the discount interval, different demand rate function which is a function of price and time is used in the model. In this regard, at first, we model the problem without regarding discount that its solution shows an impossible result in reality which the replenishment time is very short. But then with regarding discount in the model, more products are sold and thus the profit increases. Finally, we solve two numerical examples used an iterative algorithm by performing a sensitivity analysis of the model parameters and also discuss about specific managerial insights.Tue, 20 Feb 2018 20:30:00 +0100On Solutions of Possibilistic Multi- objective Quadratic Programming Problems
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In this paper, a multi- objective quadratic programming (Poss- MOQP) problem with possibilistic variables coefficients matrix in the objective functions is studied. Through the use of level sets the Poss- MOQP problem is converted into the corresponding deterministic multi- objective quadratic programming ( MOQP) problem and hence into the single parametric quadratic programming problem using the weighting method. An extended possibly efficient solution is specified. A necessary and sufficient condition for finding such a solution is established. A relationship between the solutions of possibilistic levels is constructed. Numerical example is given in the sake for the paper to clarify the obtained results.Sun, 30 Apr 2017 19:30:00 +0100Modeling and Solving a Blood Supply Chain Network: An approach for Collection of Blood
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Management of the blood as a vital and scarce resource is very important. The aim of this research is to present a novel mathematical model for designing a reliable blood supply chain network. This network consists of three main echelons including donors, collection facilities and demand points. At the collection echelon, three types of facilities are considered for receiving the bloods from the donors: main blood centers (MBCs), demountable collection centers (DCCs), and mobile blood facilities (MBFs). DCCs, and MBFs are mobile facilities that don’t have a permanent location and always move from a location to another one for collecting the bloods from the donors. The main difference between the MBFs and DCCs is that the DCCs can only visit at most a candidate location every period, but the MBFs can visit more than one candidate location in every period. Also, there is differences between their capacities and their costs. Both of DCCs and MBFs dispatch the collected bloods to the MBCs that are permanent facilities and are responsible for receiving the bloods and performing the blood transfusion process and finally sending the bloods to the demand points. Using a numerical example, the applicability of the proposed network is analyzed.Sun, 30 Apr 2017 19:30:00 +0100A New Mathematical Model for Simultaneous Lot-sizing and Production Scheduling Problems ...
http://www.ijsom.com/article_2731_506.html
This paper investigated the problem of simultaneous determination of lot-sizing and production scheduling with earliness/tardiness penalties. In this problem, decisions about lot-sizing and scheduling are made so that the sum of holding, tardiness, and setup costs is minimized. There are n orders waiting to be processed on a machine. Each order has its own due date as well as tardiness and earliness cost being the same as holding cost .Each order is delivered only once. If the production is completed before or on the due date, delivery will be on the due date. Otherwise, the order will be delivered immediately after its production is completed. In spite of its wide applications, this problem has not yet been reported in the literature. A mathematical model was presented as solution methods for the problem. Two meta-heuristics, namely, Simulated Annealing and Ant Colony System meta-heuristic algorithms are presented for solving the problem. Also, lower bounds are obtained from solving the problem relaxation, and they are compared with the optimal solutions to estimate the goodness of two meta-heuristic algorithms. They are difficult benchmarks, widely used to measure the efficiency of metaheuristics with respect to both the quality of the solutions and the central. The results show that the Simulated Annealing recorded a lower solution time and average percentage deviation than did the Ant Colony System algorithm. The presented SA is capable to solve large instances that are mostly compatible with the real-world problems.Sun, 30 Apr 2017 19:30:00 +0100Determining of an Optimal Maintenance Policy for Three State Machine Replacement Problem Using ...
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In this article, we present a sequential sampling plan for a three-state machine replacement problem using dynamic programming model. We consider an application of the Bayesian Inferences in a machine replacement problem. The machine was studied at different states of good, medium and bad. Discount dynamic programming (DDP) was applied to solve the three-state machine replacement problem, mainly to provide a policy for maintenance by considering item quality and to determine an optimal threshold policy for maintenance in the finite time horizon. A decision tree based on the sequential sampling which included the decisions of renew, repair and do-nothing was implemented in order to achieve a threshold for making an optimized decision minimizing expected final cost. According to condition-based maintenance, where the point of defective item is placed in continuing sampling area, we decided to repair the machine or to continue sampling. A sensitivity analysis technique shows that the optimal policy can be very sensitive. Sun, 30 Apr 2017 19:30:00 +0100