Multiscale production routing in multicommodity supply chains with complex production facilities

In this work, we introduce the multiscale production routing problem (MPRP), which considers the coordination of production, inventory, distribution, and routing decisions in multicommodity supply chains with complex continuous production facilities. We propose an MILP model involving two different time grids. While a detailed mode-based production scheduling model captures all critical operational constraints on the fine time grid, vehicle routing is considered in each time period of the coarse time grid. In order to solve large instances of the MPRP, we propose an iterative MILP-based heuristic approach that solves the MILP model with a restricted set of candidate routes at each iteration and dynamically updates the set of candidate routes for the next iteration. The results of an extensive computational study show that the proposed algorithm finds high-quality solutions in reasonable computation times, and in large instances, it significantly outperforms a standard two-phase heuristic approach and a solution strategy involving a one-time heuristic pre-generation of candidate routes. Similar results are achieved in an industrial case study, which considers a real-world industrial gas supply chain.     

Decomposition of information systems for production management

This paper approaches the issue of decentralization and decomposition of information systems from two angles, viz. from an organizational and from an infological point of view. Current information systems tend to become more and more integrated. However, this integration causes organizational complexity, which, in turn, becomes prohibitive for organizational change. Thus, there is a need for decomposition of the information system from an organizational point of view. A strategy for such a decomposition in a production environment is given.     

System for supply network management

Strategies and algorithms for operational planning and control are quite important to successful operations of a supply network. Implementation of a strategy requires substantial information system support, but few detailed designs of such systems have appeared in the literature. We designed an information system for a centralized management concept that could handle any type of strategy or algorithm. We developed algorithms for two different strategies deemed important by researchers and practitioners, push and pull, and implemented them in system modules. This information system performed well in simulations of the management of operations of an example six-stage supply network. This system provides an example for operational development as well as a platform for laboratory experiments.     

Towards a framework of critical success factors for implementing supply chain information systems

Supply chain information systems (SCISs) have emerged as the core of successful management in supply chains. However, the difficulties of SCIS implementations have been widely cited in the literature. Research on the critical success factors (CSFs) for SCIS implementation is rather scarce and fragmented. Therefore, the objective of this paper is to compile a framework of CSFs for implementing SCISs. Based on 10 key articles focusing on ERP implementations, we have built a list of critical success factors as a starting point for the SCIS literature search. Thereafter, based on 21 SCIS articles, CSFs for supply chain information system implementation have been defined. The analysis showed that some CSFs have been ignored and important supply chain characteristics have been overlooked. Moreover, it is not always easy for project managers to know how to implement and apply CSFs in practice.     

Optimal decisions for a two-echelon supply chain with capacity and demand information

Due to the applications of Internet of Things and big data in the Industry 4.0 context, more information in and out of a smart factory can be collected and shared between manufacturers and retailers. In this study, we consider two types of information that can be available in a supply chain consisting of a manufacturer and a retailer in Industry 4.0: the capacity information for the later rush production and the demand information shared between the retailer and manufacturer. In the supply chain, the manufacturer provides two orders with maximum limits by using a capacitated normal production and two capacitated rush production modes. To study the effects of the information, we investigate the optimal decisions and profits for the supply chain with and without the capacity information and demand information sharing. In addition, we propose a coordination mechanism for the supply chain with both the capacity information and demand information sharing. The coordination mechanism does not only rely on cost parameters, but also on the capacity and demand information. The numerical examples show that the supply chain profit can be improved by as large as 16.76% in the coordinated system, compared with the original system without the capacity information and demand information sharing.     

GBOM-oriented management of production disruption risk and optimization of supply chain construction

A generic bill-of-materials (GBOM) describes demand for materials and their proportional relations to a family of products. Supply chain constructed from the perspective of the GBOM is able to respond swiftly to market demand and lean production can be achieved by managing the total cost of supply chain effectively. Based on the GBOM, this paper examines the control of production disruption risk related to supply chain and investigates the uncertainty of production in supply chain enterprises for the purpose of achieving optimal profits in supply chain. As the production disruption risk is controlled at a certain level, the selection model of supply chain partners, which is specific and more feasible, can be constructed. A combination of random simulation and neural network is deployed to approximate uncertain function, and genetic algorithm and simulated annealing arithmetic are also used to approximately achieve the optimal scheme of supply chain construction in the context of uncertainty.     

A note on “fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain”

Liang (2008) [Liang, T. -F. (2008). A note on “fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain”. Computers & Industrial Engineering, 55, 676–694] proposed a production/distribution planning model and its solution approach in fuzzy environment. However, his mathematical model does not use backordering option. The main purpose of this paper is to demonstrate this handicap and propose a valid constraint.     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

Introducing a mixed-integer non-linear fuzzy model for risk management in designing supply chain networks

Nowadays, supply chains play an inevitable role in prompt handling of varying customers’ needs. Administration of a successful supply chain depends on how efficiently the network design is accomplished. Therefore, a supply chain network design problem is considered in this paper. The network addresses an uncertain environment threatened by different risk sources in order to captivate the real world conditions. A mixed-integer non-linear mathematical model is developed in which the uncertainties are represented by the fuzzy set theory. Benders decomposition is then applied to solve the proposed problem; consequently, the model is transformed into a mixed-integer one. Moreover, an interactive resolution method is applied to provide the decision maker with alternative decision plans in regard to different satisfaction degrees. Finally, the accuracy of the proposed model is checked by sensitivity analysis test and its performance is considered by different numerical examples.     

Impact of demand correlation and information sharing in a capacity constrained supply chain with multiple-retailers

This paper considers a single product, two-echelon capacity constrained supply chain consisting of a supplier and two retailers facing correlated end-item demand. We use a decentralized Markov decision process with restricted observations to represent this system and conduct a numerical study to quantify the benefits of information sharing to the retailers under varying levels of supplier capacity and supply allocation mechanisms. Our results show an inverse relationship between capacity and information and indicate the retailers can achieve significant benefits as a result of the information sharing partnership.     

Assessing the value of information sharing and its impact on the performance of the various partners in supply chains

With major developments in information and communication technologies, real-time information sharing becomes a significant challenge and has a considerable impact on the overall performance of supply chains. Here, we study the influence of information sharing for a monoproduct serial supply chain consisting of a supplier, warehouse, retailer and customers in the context of a decentralized decision. The objectives of this study are twofold: (1) to estimate the gains from sharing different types of information on each elementary cost and for each partner of the supply chain in detail and (2) to determine the cumulative impact of simultaneously sharing different types of information.A mathematical model is developed to assess the value of information sharing in terms of logistic costs and for different combinations related to the sharing or non-sharing of three types of upstream and downstream information: the customer demand and the supplier-warehouse and warehouse-retailer lead times. A perturbation is also injected to consider the intended or unintended distortion in the communicated information.Our study clearly showed that the gains are not cumulative when we simultaneously share different types of information. The results also highlighted the necessity to establish incentive cooperation mechanisms between the different links in the supply chain in many scenarios where the gains are not balanced. A distortion in the communicated information can also have a significant effect on the gains from sharing.     

Efficient techniques for time-constrained information dissemination using location-based social networks

Social networks have undergone an explosive growth in recent years. They constitute a central part of users׳ everyday lives as they are used as major tools for the spread of information, ideas and notifications among the members of the network. In this work we investigate the use of location-based social networks as a medium of emergency notification, for efficient dissemination of emergency information among members of the social network under time constraints. Our objective is the following: given a location-based social network comprising a number of mobile users, the social relationships among the users, the set of recipients, and the corresponding timeliness requirements, our goal is to select an appropriate subset of users so that the spread of information is maximized, time constraints are satisfied and costs are considered. We propose LATITuDE, our system that investigates the interactions among the members of the social network to infer their social relationships, and develop scalable dissemination mechanisms that select the most efficient set of users to initiate the dissemination process in order to maximize the information reach among the appropriate receivers within a time window. Our detailed experimental results illustrate that our approach is practical, effectively addresses the problem of informing the appropriate set of users within a deadline when an emergency event occurs, uses a small number of messages, and consistently outperforms its competitors.     

Risk assessment and management for supply chain networks: A case study

The aim of this study is to show how a timed Petri nets framework can be used to model and analyze a supply chain (SC) network which is subject to various risks. The method is illustrated by an industrial case study. We first investigate the disruption factors of the SC network by a failure mode, effects and criticality analysis (FMECA) technique. We then integrate the risk management procedures into design, planning, and performance evaluation process of supply chain networks through Petri net (PN) based simulation. The developed PN model provides an efficient environment for defining uncertainties in the system and evaluating the added value of the risk mitigation actions. The findings of the case study shows that the system performance can be improved using risk management actions and the overall system costs can be reduced by mitigation scenarios.     

Implementation of intelligent systems, enabling integration of SMEs to high-value supply chain networks

In the face of increasing competition from low-cost economies, European manufacturing companies are focusing on optimisation of operational activities to remain competitive. Previous work has identified how companies can optimise implementation of specialist technology to improve production capability; however increasing demands in service requirements such as customisability and flexibility are often negating the localised gains in capability.Supply chain management has become an increasingly important aspect of operations improvement to ensure support throughout the product realisation process. The key to creating a supply chain capable of this rapid response and high level of adaptability is integration of intelligent systems and management capabilities.A site-visit-based survey and characterisation of small and medium enterprises (SMEs), comprising actual or potential supply chain components, reveals that even those with well developed capabilities and attitudes to adopting production technologies are largely not proactive with technology adoption targeting these needs.A review of requirements for SMEs to achieve such competitive supply chain capabilities reveals a hierarchy of technical expertise to be developed. This is presented as an implementation strategy for staged introduction of these tools and techniques with a view to establishing high-value supply chains capable of withstanding business pressures from developing economies.     

Pricing and production decisions in dual-channel supply chains with demand disruptions

This paper develops a two-period pricing and production decision model in a one- manufacturer-one-retailer dual-channel supply chain that experiences a disruption in demand during the planning horizon. While disruption management has long been a key research issue in supply chain management, little attention has been given to disruption management in a dual-channel supply chain once the original production plan has been made. Generally, changes to the original production plan induced by a disruption may impose considerable deviation costs throughout the supply chain system. In this paper, we examine how to adjust the prices and the production plan so that the potential maximal profit is obtained under a disruption scenario. We first study the scenario where the manufacturer and the retailer are vertically integrated with demand disruptions. Then we further assume that the manufacturer bears the deviation costs and obtain the manufacturer’s and the retailer’s individual optimal pricing decision, as well as the manufacturer’s optimal production quantity in a decentralized decision-making setting. We derive conditions under which the maximum profit can be achieved. The results indicate that the optimal production quantity has some robustness under a demand disruption, in both centralized and decentralized dual-channel supply chains. We also find that the optimal pricing decisions are affected by customers’ preference for the direct channel and the market scale change, in both centralized and decentralized dual-channel supply chains.     

Designing a supply contract to coordinate supplier’s production,considering customer oriented production

This paper investigates how a manufacturer, who is trying to develop a customer-oriented production system, should design a supply contract with its component supplier. The manufacturer sells its products during a selling season, with stochastic demand and tries to coordinate supplier’s production quantity, with long lead-time, in order to provide sufficient stock. Along this line, a coordinating contract based on an option mechanism is used as the supply contract. The manufacturer’s optimal order, the supplier’s optimal production and the necessary conditions for coordination between them in the mentioned environment are obtained. Also, risk and profit sharing analysis between the contract partners is provided. A numerical example is conducted to illustrate the analysis.     

An integrated supply chain production–distribution planning with stochastic demands

In this paper a three echelon supply chain with multiple distribution centers, production sites and suppliers is modeled. For this supply chain several commodities with defined items is produced. The model is categorized as a capacitated facility location model. The hierarchical approach is used to modeling and based on decision types the model is divided into two levels. The solution approach is based on the Lagrangian Relaxation approach, improved by an efficient heuristic to solve complex sub-problems. Computational results indicated that the proposed method yields high-quality solutions within a reasonable computational time for various real size problems.     

Planning tools for managing the supply chain

In this paper, we introduce a new way to manage the supply chain. The proposed solution reduces the problem's complexity using a two-stage hierarchical production planning method and is applicable to realistic transportation optimization problems. The approach is based on planning and operations scheduling models, and is designed to minimize travel and production costs within a flexible organizational network. In the aggregate planning phase, a mathematical model involving an aggregation of products, demand and time periods is solved. It is at this initial stage that the size of the problem is reduced and its output is used as input to the detailed phase in order to improve resolution time. The second stage produces a detailed schedule. It is shown that the proposed approach generates good and feasible solutions to practical problems within a reasonable computational time.     

Issues in information systems planning

Numerous difficulties face information systems managers as they develop IS plans. Three nominal group technique sessions used IS practitioners from different levels of management to identify specific difficulties. The findings indicate a wide variety of problems faced by these managers. Top IS managers were concerned most with learning the objectives of top general management. Middle IS managers were concerned most with adopting a methodology for planning. Operating IS managers were concerned most with understanding the perceived needs of the user. These results suggest the need for more sophisticated management techniques (or the better use of existing techniques) and the need for research to address the development, utilization and evaluation of such techniques.     

Electronic commerce front-end in apparel supply chain

Information technology has been used increasingly to enhance the global competitiveness in various industries through the widespread application of cost effective electronic commerce. Many Internet-based systems have been designed and developed for supply chain management in many areas, such as publishing, computer, and garment industries. Most of them mainly center on information communication infrastructure, coordination between production and distribution, and purchasing functions with security mechanism. In this paper, we focus on the most common modules in electronic commerce front-end to conjoin various business organizations and to strengthen business competence, namely (1) an efficient web page and catalogue generator; (2) a hybrid search engine specifically for product, merchandise, equipment, and other enabling technologies; and (3) a set of tools to monitor usage patterns to further improve the web page organization. We also address the issues on implementation, examples and future directions.