European J. of Industrial Engineering (17 papers in press)
The impact of online sales in centralized and decentralized dual-channel supply chains
by Subrata Saha
Abstract: This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented.
Keywords: Supply chain management; Dual-channel supply chain; Revenue sharing contract; Pricing strategy; Stackelberg.
A blood distribution problem with new transportation options An application for the Turkish Red Crescent
by Atıl Kurt, Ferda Can Çetinkaya, Meral Azizoğlu
Abstract: This paper considers the blood distribution problem in the Central Anatolian Regional Blood Centre of the Turkish Red Crescent and proposes several demand satisfaction options considering the irradiation centres, urgent demands, and product availability. Our aim is to maximize the total weighted blood demand satisfaction. To address the problem, we develop a mixed integer linear programing model and propose a hybrid genetic algorithm. The results of our experiments have revealed that the mathematical model cannot handle even small sized problem instances in reasonable times; however, the hybrid genetic algorithm is capable of handling complex daily operations of the Turkish Red Crescent.
Keywords: blood distribution system; transportation options; vehicle routing; mixed integer linear programming model; genetic algorithm.
On an automated material handling system design problem in cellular manufacturing systems
by Woo-Sung Kim, Dae-Eun Lim
Abstract: We consider the automated material handling system design problem in a cellular manufacturing system (CMS). Simple transportation units including low-cost automated guided vehicles are quite often used in CMSs in South Korea. It is assumed that a transportation unit circulates among a group of cells (stations), and the unit is assumed to collect items from the output buffer of the stations. Collected items are unloaded at a cell which functions as a storage. We are interested in the capacity of the transportation unit, or the number of cells the transportation should visit. Using an embedded Markov chain, we derive the remaining capacity of the transportation unit when it leaves each station. In addition, the probability that the transportation unit is full at its departure epoch is also derived.We provide various numerical results including the effect of volatility of the arrival rates among stations.
Keywords: Seru Production System; Cellular Manufacturing System; Queueing Analysis; Multi-load AGV; Tandem AGV.
A coordinated production planning model with capacity expansion for supply chain networks
by Ming-Hua Lin, Jung-Fa Tsai, Pei-Chun Wang, Yu-Ting Ho
Abstract: Developing a flexible supply chain is important for enterprises to face market volatility and diversity. In order to satisfy order requirements under demand uncertainty, this study constructs a coordinated production planning model of supply chain networks considering production capacity expansion. Besides, the proposed model involves batch production that is commonly used in many companies. The constructed model is then linearized as a mixed-integer linear programming problem to guarantee global optimality. The solution of the reformulated model determines the optimal production, transportation and inventory levels as well as the optimal batch production operations and capacity expansion strategy. Several numerical experiments are conducted to demonstrate the effectiveness of the proposed method and the impacts of production capacity expansion on the operations of the supply chain.
Keywords: supply chain management; coordinated production planning model; demand uncertainty; batch production; flexible production capacity; linear transformation; deterministic optimization.
A queueing system with inventory and competing suppliers
by Mohammad Saffari, Mohsen S. Sajadieh, Farhad Hassanzadeh
Abstract: A single-server queuing system is considered where service consumes one unit of inventory which is maintained by two suppliers with different price and replenishment lead times. During inventory stockout, new customers refuse to enter the system (lost sales) but the existing ones remain in queue until inventory becomes available again (backlogged demand). We analytically derive the joint distribution of queue length and on-hand inventory in steady state and determine supplier-specific ordering policies that maximize the average system profit. A special case of the system with multiple servers is addressed. A numerical study reveals dynamics of the optimal ordering policy with respect to price and replenishment lead-times.
Keywords: Inventory; Competing suppliers; Queueing; Stationary distribution.
A green vehicle routing problem with time windows considering the heterogeneous fleet of vehicles: Two metaheuristic algorithms
by Neda Rezaei, Sadoullah Ebrahimnejad, Amirhossein Moosavi, Adel Nikfarjam
Abstract: In this paper, the green vehicle routing problem with time windows constraint is studied in the presence of a heterogeneous fleet of vehicles and filling stations. In addition, the number of vehicles and their fuel tank capacity are both limited. The main contribution of this study is the simultaneous consideration of these features, which makes the problem more practical. For this purpose, a mixed integer linear programming model that minimizes the transportation costs and 2 (or carbon dioxide) emissions, is proposed. Furthermore, a genetic algorithm and a population-based simulated annealing are developed to find high-quality solutions for large-scale instances. To validate the proposed model and algorithms, 28 instances are generated using a benchmark database. The computational results demonstrate that both algorithms provide efficient solutions regarding the objective function value and CPU time. Finally, a comprehensive sensitivity analysis is carried out to show the importance of features mentioned above.
Keywords: Green Vehicle Routing Problem; Time Windows; Heterogenous Fleet of Vehicles; Filling Station; Genetic Algorithm; Simulated Annealing.
A novel hierarchical approach for a heterogeneous 3D pallet loading problem subject to factual loading and delivery constraints
by Sena Kır, Harun Resit Yazgan
Abstract: This paper presents a hierarchical approach, which consists of a two-stage genetic algorithm and a mixed integer linear programming, for a heterogeneous three-dimensional pallet loading problem in consideration of the rotation, the relative positioning, the load-bearing strength, and the fragility constraints. Stage # 1 of the proposed two-stage genetic algorithm provides to reduce the number of items to be packed by combining similar items based on a stack-building approach. And, stage # 2 provides to estimate the number of required free pallets. After that, the proposed mixed integer linear programming solves the problem considering the findings of the proposed two-stage genetic algorithm. The proposed hierarchical approach was tested on well-known instances leading to favourable results and compared with a decent solution approach. In addition, a case study was presented.
Keywords: logistics; 3D pallet loading problem; MILP; genetic algorithm; intelligent dynamic crossover.
One approach to evaluate the influence of engineering characteristics in QFD method
by Tanja Parezanovi?, Marijana Petrovi?, Nataa Bojkovi?, Dragan Pamu?ar
Abstract: Evaluation of engineering characteristics (ECs) according to customer requirements (CRs) is the most decisive step of the house of quality in quality function deployment (QFD) method. In most cases, high degrees of correlation between ECs exist and should be modelled. The paper develops a specific measure ('influence gap') and novel underlying procedure (smallest gap technique) for ECs evaluation aiming to capture all interdependencies. The influence gap enables to characterise each EC according to its distance from ideal-maximum influence on all requirements. The relationships between CRs and ECs and their inter-relationships are obtained using interval-valued fuzzy DEMATEL method. From the practical point of view, the most important information for decision maker(s) generated by the model is the clear insight about the contribution of each EC when launching a new product/service. Practicability and usability of the proposed methodology is illustrated over a specific transportation service. [Received 6 January 2018; Accepted 2 December 2018]
Keywords: quality function deployment; QFD; DEMATEL; multicriteria decision making; MCDM; interval-valued fuzzy numbers; Smallest Gap Technique; carpooling; customer requirements; engineering characteristics.
AN EOQ MODEL FOR DETERIORATING ITEM WITH PROMOTIONAL EFFORT AND
CREDIT LINKED DEMAND
by ANINDITA KUNDU
Abstract: In the traditional supply chain models, it is observed that usually suppliers oer to the retailers a credit period and also the retailer to the customers to stimulate sales and reduce inventory. This practice of retailers increases the default risk of the percentage of customers not willing to pay back. In this paper, an inventory model has been developed under two levels of trade credit policy with customers' default risk consideration for a deteriorating item having a maximum lifetime. The supplier oers a partially permissible delay in payment per order and the retailer, in turn, provides a part of it to customers. Here, both demand and default risk are functions of the customer's trade credit period, whereas demand is also promotional eort sensitive. To mimic the changing market, the inventory costs are assumed to be imprecise. The models are illustrated numerically and some sensitivity analyses are presented.
Keywords: Two-level partial trade credit period; Promotional eort; Default risk; Time-dependent deteri- oration; Credit-sensitive demand and default risk.
A dominance-based heuristic to minimize completion time variance in a single machine system
by H.M. Soroush, Fatmah Almathkour
Abstract: This paper addresses the problem of minimizing the variance of job completion times in a deterministic single-machine scheduling system. Minimizing completion time variance is an appropriate objective in scheduling environments where service uniformity is essential. Due to the NP-hard nature of the problem, various heuristics have been presented to obtain a near-optimal solution. In this paper, we introduce a new heuristic based on some powerful precedence (dominance) relation structures, including the concepts of permanent and temporary precedence (dominance) relationships, to determine the positions of adjacent and non-adjacent jobs in a sequence. Our computational experiments demonstrate that the proposed heuristic significantly outperforms the existing ones in deriving the optimal or near-optimal solutions for three well-known sets of benchmark problems and some large randomly generated instances.
Keywords: Scheduling; single machine; completion time variance; heuristic; precedence; dominance.
Humanitarian supply chain network design using data envelopment analysis and multi-objective programming models
by Jae-Dong Hong
Abstract: Emergency events such as natural disasters or terrorist attacks seem to occur anywhere and tend to increase. This paper studies a humanitarian supply chain network (HTSCN) design problem in a pre-disaster scenario, which consists of finding the optimal emergency response facility (ERF) locations and allocation scheme of humanitarian supplies through ERFs, where all ERFs are under the risk of disruptions. Naturally, this type of design problem should deal with multiple goals. An innovative two-step framework of designing efficient HTSCN by combining multi-objective programming (MOP) models with Data Envelopment Analysis (DEA) is proposed. A case study using the historical data on the disasters in South Carolina, USA, is presented to illustrate the effectiveness and efficiency of the proposed combining framework. The case study demonstrates that the proposed procedure would help practitioners and researchers generate a finer evaluation of efficiency and would provide a benchmarking methodology for designing HTSCN system.
Keywords: humanitarian supply chain network; emergency response facility; data envelopment analysis; multi-objective programming approach.
Modelling and Optimizing the Multi-item Stochastic Joint Replenishment Problem with Uncertain Lead-time and Controllable Major Ordering Cost
by Xue-Yi Ai
Abstract: In this paper, we extend the existing stochastic joint replenishment model to a more realistic condition by considering uncertainties in lead-time and effective investment to reduce the major ordering cost. The aim is to determine the optimal strict cyclic replenishment policy and the optimal major ordering cost simultaneously to minimize the total cost. The objective cost function is approximated by expressing one element of the cost function as a Taylor series expansion. A bounds-based heuristic algorithm is then developed to solve the proposed model. The performance of the algorithm and the quality of the approximation are examined by computational experiments. The results of the models without considering uncertainty and ordering cost reduction are presented to illustrate the effectiveness of the proposed model. Experimentation and analysis of results demonstrate that the standard deviation of lead-time has a significant effect on the system.
Keywords: joint replenishment problem; stochastic demand; uncertain lead-time; inventory; optimization; major ordering cost reduction; heuristics.
Investigating the performance improvement by conversion of assembly line configuration to a pure cell system in manufacturing industry
by T... VenkataDeepthi, K. Ramakotaiah, Vijaya Kumar Manupati, Chaitanya Gangal
Abstract: Seru production systems implement reconfiguration of traditional assembly lines to a flexible cell system that aim at reducing the required workforce while at the same time augmenting the productivity manifold. For evaluating the overall performance improvement, cell formatting and assigning workers to serus takes form of a complicated decision problem. In this paper, with the objective of reducing the total cost for training the worker, minimizing the processing time and the total throughput time, mathematical insights on the solution space of a multi-objective line-cell conversion model are identified, in turn proving it to be an NP-hard model. By applying the proposed heuristic algorithm on several numerical simulations, a Pareto-optimal solution of this multi-objective model is obtained. With experimental results and comparative studies, the proposed approach proves its effectiveness that may lead to further improvement in seru production systems competitive advantage to cope with fluctuating market demands by enhancing the flexibility as well as the efficiency of the system.
Keywords: Seru; manufacturing systems; production systems; flexibility; reconfiguration; cellular manufacturing.
A new right-skewed loss function in process risk assessment
by Onur Köksoy, Pelin Ergen, Melis Zeybek
Abstract: Due to globalization, competitive companies realize that providing a more reliable, predictable, and robust product/process is a prerequisite for satisfying their customers and running a successful operation. Many quality improvement techniques focus on reducing process variation in line with the loss to society concept. The widespread use of loss functions in industrial applications has increased their popularity with different loss-handling features. Developments relating to the inverted probability density functions (pdfs) have allowed the application of particular loss functions in a wide range. This paper presents the inverted Wald loss function as a new member of the inverted probability loss family. The important features of the proposed right-skewed loss function are discussed, and the risk functions associated with some process distributions of interest are obtained. Moreover, the proposed loss function and its performance are illustrated on the basis of a comparative study and an industrial example, including the monitoring of loss.
Keywords: Asymmetric quality loss functions; inverted Wald loss function; risk function; inverted probability loss functions; Wald distribution.
Economic-statistical design of EWMA-semicircle charts under the Taguchi loss function
by Shin-Li Lu
Abstract: A single exponentially weighted moving average (EWMA) chart is effectively used to monitor the process mean and/or variance simultaneously. An EWMA-semicircle (EWMA-SC) chart designed from the economic-statistical perspective is proposed, which incorporates Taguchis quadratic loss function into Lorenzen and Vances cost model. Moreover, economic-statistical performance and the effect on process capability index are compared to those with sum of square EWMA (SS-EWMA) and maximum EWMA (MaxEWMA) charts. The optimal decision variables namely, sample size n, sampling interval time h, control limit width L, and smoothing constant - are obtained by minimizing the expected cost function. Via simulations, the EWMA-SC chart is found to incur the smallest expected cost when a process mean and variance simultaneously shift. However, the MaxEWMA chart incurs the lowest cost of defective products when a process mean shifts on its own.
Keywords: EWMA charts; Economic-statistical design; Cost model; Quadratic loss function.
Bi-objective scheduling on two dedicated processors
by Adel Kacem, Adel Dammak
Abstract: In this work, we study a bi-objective scheduling problem on two dedicated processors. The aim is to minimize the makespan and the total tardiness. Our contribution includes lower bounds for each studied criterion and a genetic algorithm adapted for the multi-criteria context. The lower bounds allows us to evaluate the quality of feasible solutions and the genetic algorithm incorporates the optimization part.We implemented our approach by considering the agregative, NSGA-II and the Pareto scenarios on a large set of instances. The obtained results show the effectiveness of the proposed algorithms.
Keywords: scheduling; total of tardiness; tasks; makespan; dedicated processors; genetic algorithms; lower bound; bi-objective; Pareto front.
QoS of cloud prognostic system Application to aircraft engines fleet
by Zohra Bouzidi
Abstract: Recently, Prognostics and Health Management (PHM) solutions are increasingly implemented in order to complete maintenance activities. The prognostic process in industrial maintenance is the main step to predict failures before they occur by determining the Remaining Useful Life (RUL) of the equipment. However, it also poses challenges such as reliability, availability, infrastructure and physics servers. To address these challenges, this paper investigates a cloud-based prognostic system of an aircraft engine based on artificial intelligence methods. We design and implement an architecture that defines an approach that is Prognostic as a Service (Prognostic aaS) using a data-driven approach. This approach will provide a suitable and efficient PHM solution as a service via internet, on the demand of a client, in accordance with a Service Level Agreement (SLA) contract drawn up in advance to ensure a better quality of service and pay this service per use (pay as you go). We esti-mated the RUL of aircraft engines fleet by implementing three techniques. Next, we studied the performance of this system; the efficient method was concluded. In addition, we discussed the quality of service (QoS) for the cloud prognostic application according to the factors of quality.
Keywords: Prognostics and Health Management (PHM); Remaining Useful Life (RUL); Prognostic as a Service; Cloud Computing; Artificial Intelligence; Measure Performance; Quality of Service (QoS).