Hybrid GA for material routing optimization in supply chain

In designing a supply chain (SC) system, the problem arises when a company has unsatisfactory inventory control policy and material routing between supplier–producer and distributor in SC considering specified cost and demand. The integration of decisions of different functions into a single optimization model is the base of this research. The aim of this paper is to study and compare the existing models of supply, production and distribution in SC and propose a model which integrates mentioned criteria in supply chain management (SCM). Furthermore, it proposes a new method for calculation of fitness function in genetic algorithm (GA) process. The successful designing of this model has led us to explore the use of heuristic methods such as GA to quantify the flow of SC, information and material flow. At first, fuzzy analytic hierarchy process (FAHP) is adapted to evaluate objective function weights in SC. Then final weights of objective function are determined by the technique for order of preference by similarity to ideal solution (TOPSIS). This research also simulated the real company SC operations, and determines the most effective strategic and operational policies for an effective SC system. The result obtained from the model shows that it is robust. This model can also be applied to other industrial environments with slight modifications.     

A statistical tolerancing approach for design of synchronized supply chains

Supply chain (SC) can be visualized as a means to fulfilling the customer's requirement with the objective to maximize the overall value generated. With the rapid change of world economy, firms need to deploy alternative methodologies to improve the responsiveness of SC. In this regard, one important issue is the synchronization and co-ordination of supply chain network (SCN). In order to ensure the dispatch of finished product to the customer, with in customers specified delivery window, with a fierce high probability, the delivery performance of any SCN is to be minimized by forcing the work in the system. These requirements can be achieved by SC coordination, where timing of the actions performed by each of the business entities must be perfectly synchronized in SCN.This research is first of its kind where a probabilistic model is conceptualized to allocate the tolerances on lead times of internal business processes of a SCN. Various linear and nonlinear constraints have been considered with an end goal of minimizing the total cost of given network. In the proposed approach, synchronization among the members of SC has been achieved in the similar fashion as that of tolerance allocation on mechanical assemblies.The effectiveness of the proposed model is illustrated with a case study. The probabilistic model for ensuring synchronization shows much promise for improving the entire performance of network in terms of greater profit, speed, flexibility, quality, and product development etc., in a long run manufacturing enterprise.     

A bi-objective integrated procurement,production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA

Efficient management of supply chain (SC) requires systematic considerations of miscellaneous issues in its comprehensive version. In this paper, a multi-periodic structure is developed for a supply chain network design (SCND) involving suppliers, factories, distribution centers (DCs), and retailers. The nature of the logistic decisions is tactical that encompasses procurement of raw materials from suppliers, production of finished product at factories, distribution of finished product to retailers via DCs, and the storage of raw materials and end product at factories and DCs. Besides, to make the structure more comprehensive, a flow-shop scheduling model in manufacturing part of the SC is integrated in order to obtain optimal delivery time of the product that consists of the makespan and the ship time of the product to DCs via factories. Moreover, to make the model more realistic, shortage in the form of backorder can occur in each period. The two objectives are minimizing the total SC costs as well as minimizing the average tardiness of product to DCs. The obtained model is a bi-objective mixed-integer non-linear programming (MINLP) model that is shown to belong to NP-Hard class of the optimization problems. Thus, a novel algorithm, called multi-objective biogeography based optimization (MOBBO) with tuned parameters is presented to find a near-optimum solution. As there is no benchmark available in the literature, the parameter-tuned multi-objective simulated annealing algorithm (MOSA) and the popular non-dominated sorting genetic algorithm (NSGA-II) are developed to validate the results obtained and to evaluate the performance of MOBBO using randomly generated test instances.     

Bi-criterion optimisation for configuring an assembly supply chain using Pareto ant colony meta-heuristic

An assembly supply chain (SC) is composed of stages that provide the components, assemble both sub-assemblies and final products, and deliver products to the customer. The activities carried out in each stage could be performed by one or more options, thus the decision-maker must select the set of options that minimises the cost of goods sold (CoGS) and the lead time (LT), simultaneously. In this paper, an ant colony-based algorithm is proposed to generate a set of SC configurations using the concept of Pareto optimality. The pheromones are updated using an equation that is a function of the CoGS and LT. The algorithm is tested using a notebook SC problem, widely used in literature. The results show that the ratio between the size of the Pareto Front computed by the proposed algorithm and the size of the one computed by exhaustive enumeration is 90%. Other metrics regarding error ratio and generational distance are provided as well as the CPU time to measure the performance of the proposed algorithm.     

基于多代理的供应链协同生产计划模型

供应链是由分布在全球的供应商、制造商、仓库、分销中心和零售商组成的复杂网络。其生产计划具有分布性,自治性,同步性和开放性等特点,使得传统的生产计划方法已经不能适应供应链的计划需求。在分析了多代理技术和供应链系统生产计划特点的基础上,采用智能代理封供应链系统的功能实体和物理实体进行封装,提出了一个基于多代理的供应链系统网络模型,并构建了基于多智能代理的生产计划运行模式。该生产计划模型分为三层：全局生产计划,企业内部子生产计划和各个任务的详细生产计划。它突破了传统生产计划的局限性,从全局规划的角度来整合供应链上的所有资源,消除了不同企业子生产计划所产生的冲突和差异。很好的体现了供应链系统信息共享和资源共享的原则。     

Knowledge management in supply chain: An empirical study from France

Supply chain management has assumed a leading operations strategy position in both manufacturing and service industries, and over the past 10 years companies have seriously implemented supply chain management strategies in their organizations. Knowledge management (KM) is a major enabler of supply chain management, and is a critical element in information intensive and multi-cultured enterprise environments. Realizing the importance of knowledge management in supply chain (SC), an attempt has been made in this paper to propose a conceptual framework for KM in SC and to validate the framework with help of an empirical study conducted with French companies. Finally, a summary of findings and conclusions is presented for KM in SC.     

A simulation model of a coordinated decentralized supply chain

This paper presents a simulation‐based study of a coordinated, decentralized linear supply chain (SC) system. In the proposed model, any supply tier considers its successors as part of its inventory system and generates replenishment orders on the basis of its partners’ operational information. We show that the proposed coordinated decision‐making process creates a reduction in information distortion along an SC compared with a traditional, noncoordinated strategy. A novel result is that we show how a coordinated SC can avoid the detrimental consequences of demand amplification in terms of penalty costs due to the stockout phenomenon in upstream stages.     

Configuration complexity assessment of convergent supply chain systems

System designers usually generate alternative configurations of supply chains (SCs) by varying especially fixed assets to satisfy a desired production scope and rate. Such alternatives often vary in associated costs and other facets including degrees of complexity. Hence, a measure of configuration complexity can be a tool for comparison and decision-making. This paper presents three approaches to assessment of configuration complexity and their applications to designing convergent SC systems. Presented approaches are conceptually distinct ways of measuring structural complexity parameters based on different preconditions and circumstances of assembly systems which are typical representatives of convergent SCs. There are applied two similar approaches based on different preconditions that are related to demand shares. Third approach does not consider any special condition relating to character of final product demand. Subsequently, we propose a framework for modeling of assembly SC models, which are dividing to classes.     

Overall performance measurement in a supply chain: towards a supplier-prime manufacturer based model

This study deals with the supply chain (SC) overall performance expression. The developed idea concerns more particularly the performance of the manufactured products. Indeed, two companies or more contribute to the manufacturing of products that are generally assembled by the prime manufacturer company. Moreover, in the industrial practice, performance scorecards are defined with regard to each process; and the overall performance is neither expressed for each company, nor for the whole SC. We propose here to identify the SC overall performance to the combination of the performances of the different involved companies in the SC. Thus, in order to obtain a definition of such performance, we choose to focus first on the performance of the prime manufacturer. In this sense, the approach is based on the SCOR model for the handling of the main processes around the considered product manufacturing. The prime manufacturer performance is then defined as the aggregation of its involved processes?? performances. While the prime manufacturer performance is strongly dependent on the suppliers?? performance, we suggest the integration of the impacting supplier performance into the prime manufacturer scorecards. From an operational point of view, the MACBETH methodology is used to coherently express both processes and overall performances. More precisely, the Choquet aggregation integral operator is applied in order to model mutual interactions between processes. Finally, the expression of a bearing??s manufacturer performance illustrates the proposition.     

A heuristic method for the inventory routing and pricing problem in a supply chain

The inventory routing problem (IRP) in a supply chain (SC) is to determine delivery routes from suppliers to some geographically dispersed retailers and inventory policy for retailers. In the past, the pricing and demand decisions seem ignored and assumed known in most IRP researches. Since the pricing decision affects the demand decision and then both inventory and routing decisions, it should be considered in the IRP simultaneously to achieve the objective of maximal profit in the supply chain. In this paper, a mathematical model for the inventory routing and pricing problem (IRPP) is proposed. Since the solution for this model is an NP (non-polynomial) problem, a heuristic method, tabu search adopting different neighborhood search approaches, is used to obtain the optimal solution. The proposed heuristic method was compared with two other methods considering the IRPP separately. The experimental results indicate that the proposed method is better than the two other methods in terms of average profit.     

An integrated multi-stage supply chain inventory model under an infinite planning horizon and continuous price decrease

This paper studies an integrated inventory model in a supply chain that involves procurement, production and delivery activities. The model is studied in an environment where products experience continuous price decrease and planning is performed in an infinite time horizon. In this model, a manufacturing facility purchases a fixed-quantity of raw materials from an outside supplier, processes the materials, and delivers a fixed-quantity of finished products to a customer periodically. In order to take advantage of the decreasing price trend, customers demand frequent deliveries of small lots of finished products, and this inventory management strategy has been used by many successful companies in technology-related industries. Therefore, the ultimate intention of this research is to study and model the inventory system for high-tech companies whose products are experiencing continuous price decrease. This model is used to determine an optimal economic lot size model for raw material procurement, production setup and finished goods delivering under an infinite planning horizon. Two efficient algorithms are developed in this paper to solve this nonlinear model and the test results consistently indicate that ordering of raw materials and delivery of finished goods should be frequent in small lots for low ordering and shipment costs. Finally an operational schedule is provided to show the implementation procedure of the model.     

SCOlog: A logic-based approach to analysing supply chain operation dynamics

In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.     

Peer‐to‐peer financing choice of SME entrepreneurs in the re‐emergence of supply chain localization

While peer‐to‐peer (P2P) financing mechanisms have recently gained significant popularity, small and medium sized enterprise (SME) entrepreneurs still harbor a considerable degree of skepticism about the role of governments in promoting alternative supply chain finance (SCF) solutions in the re‐emergence of supply chain (SC) localization. This paper studies the SC financing problem of a capital‐constrained SME entrepreneur under two alternative financing schemes provided by an online P2P lending‐investment platform, namely debt financing (DF) and equity financing (EF). Considering the competition between a local and a foreign SC in a shared market, we investigate the direct (i.e., subsidizing domestic production) and indirect (i.e., subsidizing P2P platform service fee) roles of government intervention toward SC localization. Formulating a three‐level Stackelberg game model, this paper presents a scenario‐based decision‐making framework to jointly evaluate four different SCF scenarios through the lens of local SC, P2P financing platforms, and government. The results reveal that there exist three possible regions (i.e., DF, EF, and Conflict), within which the government and the P2P financing platforms can examine the alternative SCF schemes in order to achieve a mutually agreeable agreement. Our sensitivity analysis on interest rate and exchange ratio suggests that, when financed via an online P2P lending platform (i.e., DF), the local SC always achieves a higher profit under the direct intervention policy. The indirect policy, however, is preferred only when EF is the main source of SCF and the exchange ratio is sufficiently high.     

Relation model describing the effects of introducing RFID in the supply chain: evidence from the food and beverage industry in South Korea

The development of information technology has rapidly changed the logistics industry. RFID has become more and more important in the context of supply chain management (SCM), and implementation of RFID in SCM brings with it the potential to manage the information flow and to support communication and collaboration along the supply chain. This study was conducted to build a relation model, which is a structural model, to identify the effects of introducing RFID into the supply chain of the food and beverage industry in Korea. The supply chain of the food and beverage industry was divided into five activities: procurement, production, transport, sale, warehousing, and administration. This study was based on the premise that RFID will be embedded in a transport box or pallet circulated in the SC. The model showed that SC activities have positive relationships through the RFID system, and the introduction of RFID promotes information interchanges between SC activities, which in turn enable the coordination and consolidation of a total SCM. From the results of this study, it is expected that the RFID system does not only enable the SC partners to improve their utilities but also promotes the efficiency of SCM as a whole. This is meaningful considering that there is still a controversy regarding the effects of RFID on SCM.     

An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning

In the context of supply chains operations planning, mathematical programming models have been mainly used for centralised decision-making. However, the supply chain (SC) members not always agree on the alignment of individual decisions to SC-wide objectives and are usually reluctant to share all the required SC-wide information. For these reasons, SC decentralised decision making, in which different decisional units have to be coordinated to achieve a certain level of SC performance, is the most usual situation. In this collaborative planning (CP) context, spatial and temporal integration among the different SC decisional parts has to be considered. This paper aims to develop an application which supports the integrated modelling and execution of the CP decision-making process in SCs made up of several decisional centres (DCs) which make decisions based on mathematical programming models (as in Advanced Planning Systems) under temporal and spatial integration. The described application has been used to assist the CP of a real ceramic SC. The results are also reported.     

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.     

Holonic supply chain: A study from family-based manufacturing perspective

In the contemporary business environment, to adhere to the need of the customers, caused the shift from mass production to mass-customization. This necessitates the supply chain (SC) to be effective flexible. The purpose of this paper is to seek flexibility through adoption of family-based dispatching rules under the influence of inventory system implemented at downstream echelons of an industrial supply chain network. We compared the family-based dispatching rules in existing literature under the purview of inventory system and information sharing within a supply chain network. The dispatching rules are compared for Average Flow Time performance, which is averaged over the three product families. The performance is measured using extensive discrete event simulation process. Given the various inventory related operational factors at downstream echelons, the present paper highlights the importance of strategically adopting appropriate family-based dispatching rule at the manufacturing end. In the environment of mass customization, it becomes imperative to adopt the family-based dispatching rule from the system wide SC perspective. This warrants the application of intra as well as inter-echelon information coordination. The holonic paradigm emerges in this research stream, amidst the holistic approach and the vital systemic approach. The present research shows its novelty in triplet. Firstly, it provides leverage to manager to strategically adopting a dispatching rule from the inventory system perspective. Secondly, the findings provide direction for the attenuation of adverse impact accruing from demand amplification (bullwhip effect) in the form of inventory levels by appropriately adopting family-based dispatching rule. Thirdly, the information environment is conceptualized under the paradigm of Koestler’s holonic theory.     

Simultaneous coordination of order quantity and reorder point in a two-stage supply chain

In this paper, we investigate the simultaneous coordination of order quantity and reorder point in a two-stage supply chain (SC). While coordination of order quantity has received much attention in the supply chain management literature, coordination of the reorder point has been less-studied. The retailer's reorder point has a direct impact on product availability and customer service level (CSL) and therefore has a great impact on SC profitability. Our proposed model adopts a two-stage SC with stochastic demand and lead times over multiple periods. The proposed coordination model assures global optimization of order quantity–reorder point decisions. Using a pricing scheme with a discount factor, we extract conditions in which both downstream and upstream members have sufficient motivation to participate in the coordination scheme. Numerical experiments demonstrate that the proposed model can achieve channel coordination. Results of the modeling and analyses show that coordination of both reorder point and order quantity can lead to increased SC profitability as well as CSL improvement.     

MASCF: A generic process-centered methodological framework for analysis and design of multi-agent supply chain systems

Multi-agent systems (MAS) are becoming popular for modeling complex systems such as supply chains. However, development of multi-agent systems remain quite involved and extremely time consuming. Currently, there exist no generic methodologies for modeling supply chains using multi-agent systems. In this research, we propose a generic process-centered methodological framework, Multi-Agent Supply Chain Framework (MASCF), to simplify MAS development for supply chain (SC) applications. MASCF introduces the notion of process-centered organization metaphor, and creatively adopts Supply Chain Operations Reference (SCOR) model to a well-structured generic MAS analysis and design methodology, Gaia, for multi-agent supply chain system (MASCS) development. The popular Tamagotchi case was designed and analyzed using MASCF. The validity of the framework was established by implementing MASCF output of Tamagotchi SC using the Java Agent DEvelopment Framework (JADE).     

A comprehensive decision-making model for risk management of supply chain

Risk management of a supply chain (SC) has a great influence on the stability of dynamic cooperation among SC partners and hence very important for the performance of the SC operations as a whole. A suitable decision-making model is the cornerstone for the efficiency of SC risk management. We propose in this paper a decision-making model based on the internal triggering and interactive mechanisms in an SC risk system, which takes into account dual cycles, the operational process cycle (OPC) and the product life cycle (PLC). We explore the inter-relationship among the two cycles, SC organizational performance factors (OPF) and available risk operational practice (ROP), as well as the risk managerial elements in OPC and PLC. In particular, three types of relationship, bilateral, unilateral and inter-circulative ones, are analyzed and verified. We build this dynamic relation into SC risk managerial logic and design a corresponding decision-making path. Based on the analytic network process (ANP), a methodology is designed for an optimal selection of risk management methods and tools. A numerical example is provided as an operational guideline for how to apply it to tailor operational tactics in SC risk management. The results verify that this strategic decision model is a feasible access to the suitable risk operational tactics for practitioners.