An integrated method for airline company supplier selection based on the entropy and vikor methods: a real case study

All certified airlines require to implement a safety and quality management system. Therefore, the quality of all services and products with critical operational domains have been challenging issues in the aviation industry. In this regard, supplier selection plays an important role to acquire competitive benefits. Flight operations is critical scope in an airline and their outputs have a direct impact on flight safety consequences. Therefore, the quality of supplier’s product and services play the main role in their flight operations process. In this research, a new decision-making framework is developed to evaluate the performance of the suppliers based on the Entropy and VIKOR approaches. At the outset, the main criteria and sub-criteria are identified based on the literature and expert\u27s viewpoint and then their weights are calculated using the Entropy method. Afterward, the potential suppliers are ranked using the VIKOR method. The airline supplier’s assessment through expert judgment and integrated criteria are the new approaches that are developed in this paper. The obtained results show that economic, quality and safety, and reputation respectively are the main criteria to select suppliers

An Innovation Measurement Model Based on THIO Classification: An Automotive Case Study

Many criteria have been presented so far for innovation measurement. Presenting the relation between input and output of innovation, completing other criteria and achieving more comprehensive criteria has also been raised. What is of vital importance is the right utilization of these criteria towards measuring innovation. This paper seeks to present a model to measure innovation that, in addition to the simplicity of its perception and measurement method, has an adequate comprehensiveness. The analyses are undertaken through two real case studies in automotive industry in Iran. The results show that Saipa automotive company should concentrate on Info-ware, Orga-ware and Human-ware while Iran-khodro automotive company needs to focus on Info-ware, Orga-ware and Techno-ware aspects to balance the innovation processes

Politiques de réapprovisionnement pour les produits périssable dans des conditions incertaines en considérant des critères environnementaux

The development and application of inventory models for deteriorating items is one of the main concerns of the experts in the domain, since the number and variety of deteriorating products are dramatically increasing. One of the major gaps in the deteriorating inventories literature is that researchers have not paid enough attention to two important features in their models: i) Considering stochastic conditions; especially stochastic lead time is almost overlooked since makes the mathematical challenges complicated, ii) designing innovative inventory policies by taking into account the environmental issues and particularly the CO2 emission as a new objective in a multi-objective framework that is quite new. In this thesis, we study replenishment policy for deteriorating products under stochastic conditions in form of three different problem areas. In the first one, we develop a continuous (r,Q) inventory model for a retailer that offers a deteriorating product by considering infinite planning horizon, stochastic lead time, constant demand rate and backordered shortages. For modeling the deterioration process, a non-linear holding cost is defined. Taking into consideration the stochastic lead time as well as a non-linear holding cost makes the mathematical model more complex. We therefore customize the proposed model for a uniform distribution function that could be tractable to solve optimally by an exact approach. In second problem, we study the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously for a retailer that sells a deteriorating product. Finally, in the last problem, we consider inventory and transportation costs, as well as the environmental impacts in a centralized supply chain by taking into account uncertain demand and partial backordered shortages. In order to deal with demand uncertainty, a two stage stochastic programming approach is taken. Then, by considering transportation vehicles capacity, we develop a mixed integer mathematical model. In this way, the best transportation vehicles and replenishment policy are determined by finding a balance between financial and environmental criteria. A numerical example from the real world is also presented to show the applicability and effectiveness of the proposed model.Le développement et l'application de modèles de réapprovisionnement d’articles périssables est l'une des principales préoccupations des experts en la matière, le nombre et la variété des produits périssables augmentant de façon spectaculaire. L'une des lacunes majeures dans la littérature pour la gestion des produits périssables est que les chercheurs n'ont pas accordé suffisamment d'attention à deux aspects importants dans leurs modèles: i) les conditions stochastiques ; en particulier le délai stochastique est presque négligé car rendant les défis mathématiques plus compliqués ; ii) l'élaboration de politiques innovantes de réapprovisionnement prenant en compte les critères environnementaux ; en particulier la minimisation des émissions de CO2 comme second objectif dans un contexte de modélisation multi-objectif qui est tout à fait nouvelle. Dans cette thèse, nous étudions les politiques de réapprovisionnement pour les produits périssables sous conditions stochastiques sous forme de trois problématiques différentes. Dans la première, nous développons un modèle de réapprovisionnement à révision continue (r, Q) pour un détaillant qui offre un produit périssable en prenant en compte : un horizon de planification infini, un délai d’approvisionnement stochastique, un taux de demande constante et la livraison tardive (backorder). Pour modéliser le processus de détérioration, un coût de possession de stock non linéaire est défini. La prise en considération du délai stochastique et d'un coût de possession de stock non linéaire rend le modèle mathématique plus complexe. Nous avons donc adapté le modèle proposé pour une fonction de distribution uniforme afin de résoudre de façon optimale ce problème par une approche exacte. Pour le second problème, nous étudions la stratégie de mutualisation des risques de délai de livraison par la passation de commandes de réapprovisionnement fractionnées par lots entre plusieurs fournisseurs simultanément pour un détaillant vendant un produit périssable. Enfin, dans le dernier problème, nous prenons en considération les coûts de stockage et de transport, ainsi que les impacts sur l'environnement, dans une chaîne d'approvisionnement centralisée sous condition de demande incertaine et pénurie partielle (partial backordered). Pour faire face à l'incertitude de la demande, est adoptée une approche de programmation stochastique en deux étapes. Par la suite, en tenant compte de la capacité de transport de véhicules, nous développons un modèle mathématique de programmation mixte en nombres entiers. De cette façon, les meilleurs véhicules de transport et les politiques de réapprovisionnement sont déterminés par la recherche d'un équilibre entre les critères financiers et environnementaux. Un exemple numérique du monde réel est également présenté pour démontrer l'applicabilité et l'efficacité du modèle proposé

A Bi-Objective Sustainable Vehicle Routing Optimization Model for Solid Waste Networks with Internet of Things

Waste production is growing in most communities due to population expansion. Given the stated issue, managing the Solid Waste (SW) created worldwide would be vital. Effective Waste Management (WM) is essential to preserving the environment and lowering pollution. It aids in resource preservation, greenhouse gas emission reduction, and ecosystem protection. Additionally, the promotion of public health and sanitation is significantly aided by WM procedures. This study presents an integrated procedure to enhance the operations of a WM network for recycling SW. We propose a mathematical model to find the optimal sustainable vehicle routes, allocation, and Sequence Scheduling (SS) problem in the recycling industry to reduce costs and CO2 emissions and increase job opportunities. The fundamental innovation of this work is considering waste-vehicle and waste-technology compatibility and Internet of Things (IoT) systems in the model to decrease CO2 emissions and identify compatible waste for recycling centers to produce more final products. An LP-metric and an Epsilon Constraint (EC) approach are used to solve the suggested model. By comparing the two approaches, we have found EC performs better in results and CPU time. As a result, various test problems of different sizes are offered. Accordingly, sensitivity analyses are recommended to assess the suggested model’s effectiveness. Using vehicles compatible with waste reduces CO2 emissions. Utilizing IoT technology and optimization methods makes it feasible to save costs (20%), have a less destructive impact on the environment (36%), and ultimately increase the sustainability of the WM process

A Multi-objective Multi-Supplier Sustainable Supply Chain with Deteriorating Products, Case of Cut Flowers

International audienceThere is a growing concern, in the last decade, about the environment and social footprint of business operations. The subject of supply chain sustainability, simultaneously considering economic, environment and/or social values, has gained attention in the academia and from the industry. Particularly for deteriorating and seasonal products, such as fresh produce, the issues of timely supply and disposal of the deteriorated products are of high concerns. This research develops a new replenishment policy in a centralized sustainable supply chain for the deteriorating items. The model considers inventory and transportation costs, as well as the environmental and social impacts, with several transportation vehicles producing various pollution and greenhouse gas levels. Some variables are uncertain as the end-customer demand, partial backordered ratio and deterioration rate. We also consider backorders, quantity discount prices, non-linear holding costs, multiple transportation-route options, and uncertain demand. We consider the deterioration of in-stock inventory. and the deterioration during transportation. The best transportation routes and vehicles, and inventory policy are determined by finding a balance between financial, environmental and social criteria. We develop a linear multi-objective mathematical model and present a numerical example to demonstrate its applicability and effectiveness. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

A Bi-Objective Sustainable Vehicle Routing Optimization Model for Solid Waste Networks with Internet of Things

Waste production is growing in most communities due to population expansion. Given the stated issue, managing the Solid Waste (SW) created worldwide would be vital. Effective Waste Management (WM) is essential to preserving the environment and lowering pollution. It aids in resource preservation, greenhouse gas emission reduction, and ecosystem protection. Additionally, the promotion of public health and sanitation is significantly aided by WM procedures. This study presents an integrated procedure to enhance the operations of a WM network for recycling SW. We propose a mathematical model to find the optimal sustainable vehicle routes, allocation, and Sequence Scheduling (SS) problem in the recycling industry to reduce costs and CO2 emissions and increase job opportunities. The fundamental innovation of this work is considering waste-vehicle and waste-technology compatibility and Internet of Things (IoT) systems in the model to decrease CO2 emissions and identify compatible waste for recycling centers to produce more final products. An LP-metric and an Epsilon Constraint (EC) approach are used to solve the suggested model. By comparing the two approaches, we have found EC performs better in results and CPU time. As a result, various test problems of different sizes are offered. Accordingly, sensitivity analyses are recommended to assess the suggested model’s effectiveness. Using vehicles compatible with waste reduces CO2 emissions. Utilizing IoT technology and optimization methods makes it feasible to save costs (20%), have a less destructive impact on the environment (36%), and ultimately increase the sustainability of the WM process

A Multi-objective Multi-Supplier Sustainable Supply Chain with Deteriorating Products, Case of Cut Flowers

International audienceThere is a growing concern, in the last decade, about the environment and social footprint of business operations. The subject of supply chain sustainability, simultaneously considering economic, environment and/or social values, has gained attention in the academia and from the industry. Particularly for deteriorating and seasonal products, such as fresh produce, the issues of timely supply and disposal of the deteriorated products are of high concerns. This research develops a new replenishment policy in a centralized sustainable supply chain for the deteriorating items. The model considers inventory and transportation costs, as well as the environmental and social impacts, with several transportation vehicles producing various pollution and greenhouse gas levels. Some variables are uncertain as the end-customer demand, partial backordered ratio and deterioration rate. We also consider backorders, quantity discount prices, non-linear holding costs, multiple transportation-route options, and uncertain demand. We consider the deterioration of in-stock inventory. and the deterioration during transportation. The best transportation routes and vehicles, and inventory policy are determined by finding a balance between financial, environmental and social criteria. We develop a linear multi-objective mathematical model and present a numerical example to demonstrate its applicability and effectiveness. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

A replenishment policy for perishable products with non-linear holding cost under stochastic supply lead time

International audienceAbstract

A new order splitting model with stochastic lead times for deterioration items

International audienceIn unreliable supply environments, the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously is an attractive sourcing policy that has captured the attention of academic researchers and corporate managers alike. While various assumptions are considered in the models developed, researchers tend to overlook an important inventory category in order splitting models: deteriorating items. In this paper, we study an order splitting policy for a retailer that sells a deteriorating product. The inventory system is modelled as a continuous review system (s, Q) under stochastic lead time. Demand rate per unit time is assumed to be constant over an infinite planning horizon and shortages are backordered completely. We develop two inventory models. In the first model, it is assumed that all the requirements are supplied by only one source, whereas in the second, two suppliers are available. We use sensitivity analysis to determine the situations in which each sourcing policy is the most economic. We then study a real case from the European pharmaceutical industry to demonstrate the applicability and effectiveness of the proposed models. Finally, more promising directions are suggested for future research

Developing and analyzing two inventory models for deterioration items under stochastic supply lead time

International audienc