Technical Sessions A2 - G2
SESSION A2: Applied Operations Research
 SEQUENCING MULTI-MIXED-MODEL ASSEMBLY LINES: AN APPROACH VIA CLUSTERING SEARCH
Mariana M. Ushizima, Fernando A. S. Marins, Antonio A. Chaves, Alexandre Leme Sanches and José Arnaldo B. Montevechi
Since lean manufacturing concepts have been adopted, several studies dealing with the effective utilization of Mixed-Model Assembly Lines (MMAL) have focused on the sequencing of such lines. The MMAL must have flexibility to produce different models in given sequences and obtain benefits, such as constant consumption of parts or subassemblies, thus minimizing the scaling of Kanban, the intermediate stocks, and the workload level at each station to minimize line stoppages. In situations where it is possible to produce many different models, production based on market forecast becomes unviable, even with the use of computational resources, which makes the products’ sequencing in the MMAL a differential. This paper deals with the MMAL in multiple lines in a lean manufacturing environment, where an operational structure of several domestic suppliers supports many MMAL simultaneously, so that all the assembly lines can receive parts or sub-assembly from all the suppliers. To optimize this system, the sequencing must seek to minimize the distance between the real consumption and the constant ideal consumption of parts or subassemblies, thereby reducing the scaling of Kanban and intermediate stocks. To solve the sequencing problems, the Clustering Search (CS) was applied. Instances from the literature and also generated instances were tested, thus allowing to comparing the method with other methods presented in the literature. Analysing the results obtained, it was observed that the CS was efficient, obtaining good solutions in less time.
 LAGRANGIAN RELAXATION DOMINANCE BASED HEURISTIC FOR SOLVING A SHORTEST PATH PROBLEM WITH RESOURCES CONSTRAINTS
Abdelkader Lamamri, Anass Nagih and Hacene Ait Haddadene
The shortest path problem with resource constraints (SPPRC) consists of finding the minimum cost path between two specified points while respecting constraints on resource consumption. The presence of resource consumption constraints makes the (SPPRC) an NP-hard problem in the ordinary sense. In this paper, we present and compare the efficiency of exact and approximate solution methods. The first method is the well known exact dynamic programming based algorithm, the second method consists of the dominance only on a subset of resources while respecting all resource constraints, and the third method is a Lagrangian relaxation based algorithm. The experimental comparison of these three methods favors the approach using Lagrangian relaxation.
 ON BALANCING BICYCLE SHARING SYSTEMS : A HYBRID GA FOR SOLVING THE MULTIPLE VEHICLES ROUTING PROBLEM
Kadri Ahmed Abdelmoumene, Kacem Imed and Labadi Karim
In recent years, bicycle sharing systems have experienced a significant growth as an alternative to motorized transportation systems in dense areas, offering people an ecological, fast and flexible mean to perform short trips. The crucial factor for the success of such systems is its ability to satisfy the stochastic demands of users by ensuring the availability of bicycles for peak or empty places to return them at each station all the day long. To achieve such an objective, inventory rebalancing operations are done with some vehicles which are driving around the city and move bicycles from a station to another. In this work, we address the rebalancing problem with multiple vehicles considering the static case. We present a mathematical formulation for the problem and we develop an hybrid genetic algorithm based on the local search method which provides improved solutions compared to the classical genetic algorithm in a reduced computational times.
 Bees Swarm Optimization metaheuristic Guided by Decomposition for solving MAXSAT
Youcef Djenouri, Zineb Habbas and Wassila Aggoune-Mtalaa
Decomposition methods aim to split a problem into a collection of interconnected clusters. Many
research studies have explored decomposition methods, especially the tree-decomposition for its good theoretical properties, within complete methods. More recently, the tree decomposition has been successfully used to guide the Variable Neighbour Search (VNS) local search method. This present work follows this last direction and proposes two approaches called BSOGD1 and BSOGD2 to guide the Bees Swarm Optimization (BSO) metaheuristic with a decomposition. This paper deals with the MAX-SAT problem and uses the Kmeans algorithm for the decomposition phase. Several experimental results conducted on DIMACS benchmarks and some other hard SAT instances lead to
promising results in terms of the quality of the solutions. Moreover, these experiments highlight a good stability of the two approaches, more especially, when dealing with hard instances like the Parity8 family from DIMACS. Beyond these first promising results, note that this approach can be easily applied to many other optimization problems such as the Weighted MAX-SAT, the MAXCSP
or the colouring problem and can be used with other decomposition methods as well as other metaheuristics.
SESSION B2: Transportation Systems
 A multi-objective optimization for handicapped person transportation
Mohamed Amine Masmoudi, Wu Peng, Chu Feng and Abdelaziz Dammak
This paper studies a multi-objective handicapped person transportation (HPT) problem, which aims to design the routes of a fleet of vehicles to satisfy a set of transportation requests with specified pickup and delivery locations, while respecting vehicle capacity, route duration limitation, pickup and delivery time windows, and precedence constraints. The two objectives are to minimize the total routing distance and the users’ waiting time aboard the vehicles, respectively. The problem can be considered as a generalization of the pickup and delivery problem with time windows (PDPTW) that is known to be NP-hard. To solve the considered problem, a multi-objective genetic algorithm (MOGA) combining Pareto dominance method is proposed. Computational experiments indicate the effectiveness of the proposed algorithm.
 A hybrid algorithm for a static dial-a-ride problem
Mohamed Amine Masmoudi, Chu Feng, Wu Peng and Abdelaziz Dammak
This paper studies a handicapped person transportation problem, which aims to plan efficient routes for the disabled transportation from specified origin points to specified destination points by a fleet of vehicles with wheelchairs. Such transportation problem has to respect the limits of the maximum route length, the maximum user ride time and the required time windows. It can be modeled as a static dial-a-ride problem (DARP) that is known to be NP-hard. For this problem, a hybrid algorithm combining Genetic Algorithm (GA) and Reduced Variable Neighborhood Search (RVNS) is developed to obtain its near-optimal solution, in which the RVNS is used to improve the quality of the solutions generated by the GA. Moreover, a simple constructive method is proposed to obtain high-quality initial population and a new crossover operator for the GA is adapted to the problem. Computational results on benchmark instances with up to 13 vehicles and 144 requests show that the proposed algorithm outperforms the recently proposed hybrid Large Neighborhood Search (LNS) algorithm.
 TWO-ECHELON VEHICLE ROUTING PROBLEM WITH SIMULTANEOUS PICKUP AND DELIVERY: MATHEMATICAL MODEL AND VALID INEQUALITIES
Onder Belgin, Ismail Karaoglan and Fulya Altiparmak
As one of the most important areas of logistics management, vehicle routing is well-known combinatorial optimization problem. In this study a variant of vehicle routing problem called two-echelon vehicle routing problem with simultaneous pickup and delivery (2E-VRPSPD) is considered. The 2E-VRPSPD performs the pickup and delivery activities simultaneously by the same vehicles through depot to satellites in the first echelon and from satellites to customers in the second echelon. In this study, we propose a node-based mathematical model for the problem and three valid inequalities adapted from the literature to strengthen the model. Computational results are provided to demonstrate the effectiveness of the proposed mathematical model.
 THE MULTI-DEPOT TOPOLOGY FOR THE AUTOMATED TRANSIT NETWORK PROBLEM
Jouhaina Chaouachi and Olfa Chebbi
Automated transit network is a public transportation service that uses a set of driverless vehicles
to move people between a set of predefined stations. In this paper, we focus on routing automated
transit network vehicles in a network with multiple depots topology. More specifically, we focus
on the empty vehicles redistribution problem related to automated transit network. We define the
routing problem and present a genetic approach to deal with it. Computational results made on
generated instances inspired by a real case study prove the efficiency of our algorithm.
SESSION C2: Supply Chain Management & Logistics
 CONCEPTION AND IMPLEMENTATION OF A DECISION SUPPORT SYSTEM HEURISTIC FOR SELECTING MEDICINES SUPPLIERS IN THE HOSPITAL SECTOR
Kaoutar Jenoui and Abdellah Abouabdellah
The purchasing function is the strongest link in hospital supply chain. The stakes which are related to it are often complex and difficult to define. Public institutions and hospitals are all invited to master these link operations, with particular focus on the hospital-supplier relationship. One of the most crucial is the selection of the right supplier, which is based on both qualitative and quantitave criteria. However, few methods and tools are available to guide the decision maker to make optimal choices based on different types of criteria. Therefore, we propose in this paper a new heuristic for a common optimization work between hospitals and suppliers, in order to create a value control in costs, deadlines and quality. Our paper is composed of five parts. The first presents the literature review. The second explains the problematic situation. The third sets out our work methodology and the proposed model. In the fourth part, we illustrate the proposed methodology through a case study. And we finish our paper with a conclusion and work prospects.
 A SPARE PART INVENTORY MANAGEMENT PROBLEM CONSIDERING REGION STOCK COORDINATION
Donghai Wang and Qiuhong Zhao
The spare part inventory management problem often puzzles managers and researchers. This work considers a two-echelon maintenance network which consists of a factory (central warehouse) and a number of repair shops (local warehouse). To reduce emergency shipment costs of the network, the paper presents a region stock coordination mechanism within repair shops. Considering normal shipment cost, emergency shipment cost, stock transfer cost and inventory cost, a region stock coordination model of repair shops is established. Finally, we take a numerical analysis to verify the validity of the proposed model. The result shows that the proposed model reduces both the total costs and the total inventory level of the maintenance network.
 SUPPLY CHAIN OF BLOOD PRODUCTS AND ITS OPTIMIZATION
Imane Hssini, Nadine Meskens and Fouad Riane
The optimization of the supply chain of blood products is a challenge for managers of blood banks who seek to ensure the right product in the right quantity at the right time. In this paper, we focus on the simultaneous optimization of the storage and distribution of blood products. We will address this problem by introducing two literature reviews, the first one is about the researches concerning the blood products inventory and distribution processes and the second one relates to various works dealing with IRP problems. After that we develop a mathematical model which describes several constraints related to our problem. With this work, we aim to determine for each period of the day, the routing to be performed by each vehicle as well as the quantities of products to be delivered in order to minimize costs for transport and storage without shortage. This study will focus on the Belgian supply chain.
 THE IMPACT OF PROMOTIONAL SIGNS ON NEWSBOY’S ORDERING DECISION
Hexin Wang and Fei Qi
Promotion is an important practice in marketing practice. How to carry out promotion and achieve the ideal effect is always the focus of the retailers. This paper looks at the influence of promotional signs on purchasing decisions in newsvendor problems, and focus on “bounded rational decision”. We adopt empirical research methods, design experiments from the perspective of retailers and simulate a two-phase newsvendor setting with the expected rise of procurement prices. Through the statistical analysis of subjects’ actual ordering quantity of goods, the effect of promotional signs on retailers’ ordering decisions is studied. We then analyze the results under different settings of factors, and explain the possible reason why the differences are produced. The results show that people are bounded rational in actual decision-making, and their decisions are affected by psychological suggestion, which can lead to decision bias.
SESSION D2: Computers & Industrial Engineering in fashion industry
 DESIGNING OF VIRTUAL SYSTEM “FEMALE BODY-DRESS” WITH HUMAN FRIENDLY CONTENT
Victor Y. Kuzmichev and Guo Mengna
Nowadays, the booming of 3D simulation and analog technology have provided powerful support for the CAD improvement. Simulation results related to the clothing are expected not only be able to predict the clothes shape with highly accuracy according to 2D flat pattern and material properties, but also start to focus on prediction of compression pressure in system ""body-clothes"". In this study we showed the initial steps and content of “human-friendly” CAD (HF CAD) for system “female body - dress”, which was created by combining the different data bases obtained from the pattern block parameters, fabric properties, 3D air gape located between the body and clothes (CEV), comfort perception under acting of pressure to soft tissue. Under this way, we tried to improve the existing apparel CAD with function to predict the subjective perception of physical pressure.
 MEN UNDERWEAR DESIGN – MAIN PROBLEMS AND SOLUTIONS
Kuzmichev Victor and Cheng Zhe
This research devoted to the problems arising in the process of male underwear designing. To improve the situation it’s necessary to renew and increase all the data bases. 1st data base is about male body, its structure and body sizes, morphology, sensitiveness of soft tissue under compression pressure done by knitted materials, elasticity of soft tissue and ability to reshaping to get push-up effects. 2nd data base is about the knitted textile material, its properties including comfort, elongation, ability to compress and reshape the soft tissue, and way of using the properties mentioned in pattern block design. 3rd data base is about the structure of underwear including the number of details, inner seams configurations to help the body compression. We have found out some significant relations between these parameters from mentioned data bases and establish into the system, which can provide the new algorithm of pattern block making.
 MODIFICATION OF PATTERN BLOCK FOR GETTING THE SIMILAR SILHOUETTE FOR SYSTEM "FEMALE BODY IN DIFFERENT SIZES - CLOTHES"
Olga Surikova, Victor Kuzmichev and Galina Surikova
The factors that influencing on front silhouettes of female clothes were studied from 36 to 56 size (in accordance with the French sizing system). The main factors which have strong impact on the front view of clothes are the eases to waist girth, hip girth and to shoulder length designed in basic pattern block. Clothes silhouette is changed sharply if the clothes was made by using the basic block with the equal ease values designed in all body sizes. To get the similar silhouette for all body sizes, we are established the method of ease allowance adopted separately for each size.
 BUILDING AN INTELLIGENT COLLABORATIVE GARMENT DESIGN PLATFORM BY CONTROLLING HUMAN PERCEPTION ON 3D VIRTUAL PRODUCTS
Xiao Chen, Xianyi Zeng, Ludovic Koehl and Xuyuan Tao
This paper proposes a web-based collaborative garment design platform on which the designer and consumer can communicate on a personalized 3D virtual product and jointly adjust its perception according to the wearer’s body shape and his/her specific fashion requirements. For this purpose, a 3D garment CAD software is first selected so that the designer can easily design a series of virtual products. Compared with similar existing work, the original contributions of our study include: 1) quantitative identification of human perception on virtual products using sensory analysis, and 2) adjustment of technical design parameters according to desired consumer’ perception. In this context, we propose an active learning-based experimental design in order to find the most appropriate values of the fabric technical parameters permitting to minimize the overall perceptual difference between real and virtual fabrics in static and dynamic scenarios. Also, we extract normalized tactile and visual sensory descriptors characterizing human perception on the concerned fabric samples. In the collaborative design process, these normalized descriptors will be used for communications between the designer and the consumer for determining the final product. By learning from the experimental data on identified inputs (fabric parameters) and outputs (sensory descriptors), we model the relationship between fabric technical parameters and human perception on finished virtual fabrics. The method of fuzzy ID3 decision tree has successfully been applied in this modeling procedure. According to the same principle, we build another model for characterizing the relation between garment pattern parameters and human perception on garment fitting. These two models, combined with the corresponding garment CAD software and the learning data acquired from the sensory experiments, constitute the main components of the web-based collaborative garment design platform.
SESSION E2: Heuristics and Approximation Algorithms for Scheduling Problems
 CREATING TIMETABLES IN CASE OF DISTURBANCES IN SIMULATION OF RAILROAD TRAFFIC
In this paper a traffic-control algorithm is designed that creates a feasible traffic plan when normal schedules are somehow disturbed in a train traffic simulation environment. The main questions That are handled in this algorithm are: (1) when must the decision be made to make a new traffic plan? and (2) How to create the new traffic plan? First conflict probabilities are introduced to model the timing of the new traffic plan. Next a method is presented to create a new traffic plan in case of small disturbances, based on finding a maximum weighted clique in a graph. The presented algorithm works fast enough to be used in simulation.
 Mixed integer programming formulations for the single processor scheduling problem with time restrictions
Rachid Benmansour, Oliver Braun and Abdelhakim Artiba
In the single-processor scheduling problem with time restrictions that has been formulated at first by Braun, Chung and Graham , n independent jobs have to be processed non-preemptively on a single processor that can handle only one job at a time, subject only to the following constraint: during any time period of length a > 0 the number of jobs being executed is less than or equal to a given integer value B>=2. This constraint reflects the condition that each job needs one of B additional resources for being processed and that a resource has to be renewed after the processing of a job has been finished. The jobs are simultaneously available for processing at the beginning of the planning horizon, and their processing times are fixed and known in advance. The objective is to minimize the completion time of the last job in the optimal sequence (i.e. the makespan).
 AN IMPROVED MULTI AGENT PARTICLE SWARM OPTIMIZATION TO SOLVE FLEXIBLE JOB SHOP SCHEDULING PROBLEM
Maroua Nouiri, Abdelghani Bekrar, Abderrazak Jemai, Damien Trentesaux, Ahmed Chiheb Ammari and Smail Niar
Many efficient meta-heuristics methods are developed to solve Flexible Job Scheduling Problem (FJSP) to get nearly optimal solutions that optimize an objective function. However, in real-world manufacturing systems, schedules are often confronted with uncertain factors such as random machine breakdown. Therefore, centralized approaches are in general inflexible, expensive, and slow to satisfy scheduling problems under disruptions. For a better efficiency targeting such situations, distributed approaches based on Multi-Agent System methods and using metaheuristics have attracted more attention. In a previous work, we have proposed a Multi-Agent Particle swarm optimization named MAPSO2 algorithm to solve FJSP. Despite of the promising results obtained in the proposed model in term of solution quality, some limitations have been detected. In this paper, we present an improved MAPSO2 named _MAPSO2_^+ to solve FJSP with better flexibility.
 STATISTICAL LEARNING VERSUS MACHINE LEARNING: INTEGRATING ESTIMATION OF DISTRIBUTION ALGORITHMS VERSUS Q-LEARNING INTO META-RAPS
Arif Arin and Ghaith Rabadi
Finding near-optimal solutions in an acceptable amount of time is a challenge when developing sophisticated approximate approaches. A powerful answer to this challenge might be reached by incorporating intelligence into metaheuristics. We propose integrating two methods into Meta-RaPS (Metaheuristic for Randomized Priority Search), which is currently classified as a memoryless metaheuristic. The first method is the Estimation of Distribution Algorithms (EDA), and the second is utilizing a machine learning algorithm known as Q-Learning. To evaluate their performance, the proposed algorithms were tested on the 0-1 Multidimensional Knapsack Problem (MKP). Meta-RaPS EDA appears to perform better than Meta-RaPS Q-Learning. However, they both showed superior performance to other approaches presented in the literature for the 0-1 MKP.
SESSION F2: Supply Chain Management & Logistics
A MIP MODEL FOR MULTI-PERIOD MULTI-ITEM CAPACITATED INVENTORY TRANSPORTATION PROBLEM OF FOODGRAINS FOR INDIAN PDS
Ajinkya Tanksale and J. K. Jha
In this work, we study a multi-period multi-item capacitated inventory transportation problem of foodgrains in case of public distribution system (PDS) in India. To make the PDS work, Food Corporation of India (FCI) is the central nodal agency which undertakes the procurement, storage and transportation of foodgrains over a large geographical area. In this work, we investigate the problem of inventory transportation of foodgrains faced by FCI for Indian PDS. The problem is to find the optimal amount of foodgrains to be stored in each warehouse and transported among the warehouses to meet the demand during each period. A mixed integer programming model is presented to minimize the total cost of inventory holding and foodgrains transported during each period over a finite planning horizon considering the constraints on storage capacity of warehouses and available capacity of transportation modes. The proposed model is solved using IBM ILOG Cplex V 12.5 optimization package for small size problems and the results are presented which would help FCI to plan the monthly storage and movement of foodgrains.
 A RETAILER-SUPPLIER SUPPLY CHAIN MODELS WITH TRADE CREDIT DEFAULT RISK UNDER A SUPPLIER-STACKELBERG GAME
Chengfeng Wu and Qiuhong Zhao
The purpose of the paper is to formulate a retailer-supplier uncooperative replenishment models with the demand and default risk are trade credit functions for determining trade credit strategy under a supplier-Stackelberg model. We first present optimal results of decentralized and centralized decision without trade credit. Then, we derive the existence and uniqueness conditions of the optimal solutions for the retailer and the supplier. Moreover, we develop a set of theorems and corollary to determine the optimal solutions.
 Value Analysis Dashboard in Supply Chain Management
Seyedehfatemeh Golrizgashti and Seyedali Dalil
Value creation is broadly seen as an essential component of competitiveness in manufacturing industries. The Goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders in supply chain via balanced scorecard approach. The key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for stakeholders in supply chain. Structural Equation Modeling has been used to disclose relations between value indicators and balanced scorecard metrics via supply chain. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. The result shows the most important balanced scorecard metrics that can create more value for key stakeholders in supply chain. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.
 Proposing a resilient reschedule design in liner shipping considering two recovery strategies and CO2 emissions
Sogol Saremi and Farshid Evazabadian
Every day thousands of containers arrive at sea ports from countries all around the world. They are carried abroad liner ships, which offer regularly scheduled services on fixed routes. Alleging services respondent to the predetermined schedule is epochal in order to humour consignees; however, disruptions are inescapable in a voyage. In this paper a MILP model have presented to reschedule disrupted liner ships or the ones impacted indirectly merely to reserve weekly services. Spotting omitting a port call and speeding up the ships will allow us to track fuel inventory level of the ships, so their fuel costs have been considered as well. The model is applied on a real life case of Iran liner shipping lines and their reschedule plan is obtained by solving this model on a CPLEX GAMS solver in less than a minute. Results show the dominance of speed increment strategy in most planning days. Moreover, sensitivity analysis conducted on fuel inventory level shows the inevitable fuel price and primal inventory level's influx on ships' costs. Sensitivity analysis on unavailability duration of the ships also suggests that Substantial changes in the objective function caused by omitting the port calls rather than speeding up the ships
SESSION G2: Supply Chain Management & Logistics
Supply chain configuration for diffusion of new Product.
Jmal Rim, Dammak Abdelaziz and Kharrat Aida
We propose a mathematical model supply chain configuration of a new product.Which integrates the outsourcing constraint in both product life cycle phases, production and diffusion. Knowing that is uncommon, the studie’s that consider the outsourcing constraint in the product life cycle configuration .The proposed model is applied in practical case to with several scenarios to identify the optimal plan which define the correct quantities to be produced or distributed with company resources and those to be outsourced to maximize the company’s net revenue.
MULTIDIMENSIONAL FAILURE PROBABILITIES BASED ON SYMMETRIC AND ASYMMETRIC PRODUCT CHARACTERISTIC DISTRIBUTION MODELS WITHIN HIGH-PRECISION MANUFACTURING PROCESSES
Stefan Bracke and Bianca Backes
The modern industrial production development is characterised by the manufacturing in complex value added networks. In fact, the manufacturing process of complex technical products depends on the OEM and a rising number of suppliers.
Against this background, manufactures and suppliers need indices and factors respectively to allow the assessment and validation of manufacturing processes within value added networks. Manufacturing processes of technically complex products require highly standardized methods to fulfil technical and customer specifications. To accomplish the demanded specifications, various methods, which can be applied at different phases of the product life cycle, have been developed. One of these methods, within the manufacturing phase, is the process capability index (PCI). The determination of the PCI allows the visualisation of risk with one indicator and failure probability with regard to a manufacturing process. State-of-the-art is the univariate calculation of the PCI based on the analysis of one product characteristic. However, risks of complex manufacturing processes generally depending on more than one product characteristic. The analysis of manufacturing processes and the attendant process optimization actions leads to a reduced amount of production failures and therefore to a reduced manufacturing risk and reliable products. Therefore, the focus of the research work is the development of an approach to determine a multidimensional PCI (MPCI) as an analogon to the common, univariate PCI. Precondition for the determination of PCI or MPCI are capable measurement systems and machine tools.
This paper outlines different approaches for the determination of multidimensional process capability indices based on symmetric and asymmetric product characteristic distribution models. Based on this theoretical MPCI determination procedure, the application of the included algorithms and methods is shown within a case study ‘dental shape drill tool’ on the bases of a prototype pre-production data set, which includes real effects of typical manufacturing chipping processes.
A MODELING FRAMEWORK BASED ON SCOR MODEL TOWARDS SUPPLY CHAIN RISK MANAGEMENT
Saleh Eddine Ben Jbara, Pierre David and Gülgün Alpan
A supply chain (SC) is an adaptive and complex system of systems. Every actor of the chain may experience abnormal conditions (a disruption, distorted data, etc.) that may lead to negative effects on the performance. It’s important for a company to know how different functional and physical subsystems react face to risk events. Modeling is an effective approach to capture the complexity of the supply chain behavior. In this article, we propose a modeling framework that has the advantage to capture supply chain behavior under risk. It is based on a meta-model that uses the SCOR model as a basis. It defines a set of generic constructs that provide flexibility and modeling ease for supply chain practitioners. The constructs are structured into organization and execution constructs. The organization constructs capture the different functionalities of supply chain actors, while the execution constructs capture various ways of execution of supply chain actors’ functionalities. An automotive parts supply chain is modeled to illustrate the proposed framework. The originality of this framework is two-fold: it provides SC practitioners with a library of building blocks that support modeling scenarios and it facilitates the inclusion of SC risk management issues at the modeling phase.
An Ordering Policy in a Serial Two-echelon Inventory System to Eliminate the Uncertainty in Upstream Demand
This paper considers a serial two-echelon inventory system with one warehouse and one retailer. Customers arrive to the retailer according a Poisson process, and unsatisfied demand will be lost. The retailer replenishes its stocks from the warehouse. We assume that the retailer applies the (1, T) ordering policy to eliminate the uncertainty in demand for the warehouse. In this ordering policy the retailer orders one unit at each fixed time interval to the warehouse. Because under such an ordering policy the demand processes of the all upstream echelons are deterministic, the standard lot sizing model can be applied in the warehouse. In this paper we calculate the total cost of the inventory system, discuss about its convexity conditions, and present a procedure to obtain optimal fixed time interval between two consecutive orders of the retailer and optimal lot size of the warehouse. We also show that the presented procedure is convergent.