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Genetic algorithms for advanced planning and scheduling in supply networks - ebook/pdf
Genetic algorithms for advanced planning and scheduling in supply networks - ebook/pdf
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Advances in intelligent methods have significantly modified the business organization of enterprises and the way they do business. The efficient management of the new form of business needs new tools. Therefore, this book presents an optimization method with genetic algorithms for operating decision making in supply networks.
This book focuses on both the theory and applications of genetic algorithms for planning and scheduling in supply networks and is divided into two parts. Part I presents the general aspects of the supply network management, with background information on the planning and scheduling methods. The main objective of studies presented in Part I is to analyze the concept and forms of inter-organizational cooperation from a viewpoint of the operating decision making.
Part II introduces to genetic algorithms and presents their applications. The theoretical side deals with the procedures of genetic algorithms, representation, selection and genetic operators. The purpose of this book is to pay special attention to applications of genetic algorithms to the supply network planning and scheduling. The applications of genetic algorithms concern mainly production environments.

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46 PLN Anna Ławrynowicz attained her higher education in the field of Technology at the Poznan  University of Technology. She received a PhD from the Poznan University of Economics.  In 2007, she qualified as an Assistant Professor in the field of Economics at the Wroclaw  University of Economics. Recently, she has worked as a professor at the Enterprise Institute  in the Warsaw School of Economics. Since 2011 she is a professor at the Department of  Production Management at the Warsaw University of Technology. Between 1994 and 1996, she was the co-founder and member of the Management Board of  Comarch S.A. in Krakow. Currently, she is a member of the Supervisory Board of Comarch  S. A. in Krakow (from 2004). Anna Ławrynowicz is a member of The Operational Research Society in Birmingham, U.K  and the Emerald Literati Network in United Kingdom. She is the author of over seventy  publications, both in Poland and abroad, in the domains of Information Technology and  Management. Advances in intelligent methods have significantly modified the business organization of  enterprises and the way they do business. The efficient management of the new form of  business needs new tools. Therefore, this book presents an optimization method with genetic  algorithms for operating decision making in new structures of business.  This book focuses on both the theory and applications of genetic algorithms for planning and  scheduling in supply networks.  This book is divided into two parts. Part I presents the general aspects of the supply network  management, with background information on the planning and scheduling methods. The  main objective of studies presented in Part I is to analyze the concept and forms of inter- organizational cooperation from a viewpoint of the operating decision making. Part II introduces to genetic algorithms and presents their applications. The theoretical  side deals with the procedures of genetic algorithms, representation, selection and genetic  operators. The purpose of this book is to pay special attention to applications of genetic algorithms to  the supply network planning and scheduling. The applications of genetic algorithms concern  mainly on production environments. Difin ul. Kostrzewskiego 1, 00-768 Warszawa tel. 22 851 45 61, 22 851 45 62 fax 22 841 98 91 www.difin.pl ISBN 978-83-7641-778-3 G e n e t i c A l g o r i t h m s f o r A d v a n c e d P l a n n i n g a n d S c h e d u l i n g i n S u p p l y N e t w o r k s D i f i n A n n A Ł Aw r y n o w i c z GeNetic AlGorithmS for advanced planning and Scheduling in Supply networkS Difin Reviewed by prof. dr hab. Wiesław Grudzewski Publication funded by the Warsaw University of Technology. Copyright Difin SA Warsaw 2013. All right reserved. No portion of his book may be reproduced, by any process or technique, without the express written consent of the publisher. Wszelkie prawa zastrzeżone. Kopiowanie, przedrukowywanie i rozpowszechnianie całości lub fragment(cid:243)w niniejszej pracy bez zgody wydawcy zabronione. ISBN 978-83-7930-426-4 Printed in Poland Copyright Difin SA., Warsaw 2013. 00-768 Warsaw, ul. F. Kostrzewskiego 1, tel. 22 851-45-61, 22 851-45-62, fax 22 841-98-91 DTP: Z. Wasilewski, Warsaw CONTENTS Introduction PART I. BASICS OF THE SUPPLY NETWORK MANAGEMENT 1. Theoretical foundations of the production in network 1.1. Definition of key terms 1.2. Supply network management 2. Planning and scheduling in production environments 2.1. Production planning 2.2. Production scheduling 2.3. Advanced planning and scheduling 2.4. Planning and scheduling methods PART II. GENETIC ALGORITHMS AND THEIR APPLICATIONS 3. Introduction to genetic algorithms 3.1. Terms and definitions 3.2. Procedure of the genetic algorithm 3.3. Representation 3.4. Selection 3.5. Crossover operators 3.6. Mutation 7 11 13 13 20 24 24 29 38 41 47 49 49 51 57 59 62 67 6 Contents 4. Optimization of the supply network configuration 4.1. Genetic algorithm for the plant layout problem 4.2. Facility layout optimization using genetic algorithms 4.3. Grouping of parts and machines by genetic algorithms 5. A review of the evolutionary-based methods for planning and scheduling 5.1. Applications of genetic algorithms for solving production planning problems 5.2. Development of genetic algorithms for production scheduling problems 5.3. Using genetic algorithms to solve the lot-sizing problem 5.4. Assembly line balancing problem with genetic algorithms 6. New approaches to planning and scheduling in supply networks 6.1. Hybrid approach with an expert system and a genetic algorithm to production 6.2. An application of the genetic approach for advanced scheduling in industrial management clusters 6.3. A two-phase system for planning and scheduling in an industrial cluster 6.4. A novel intelligent method to support operations management in clusters Summary and conclusions References Appendix: Production plans 72 72 77 80 88 88 91 117 118 122 122 136 151 166 178 180 195 INTRODUCTION Advances in intelligent methods have significantly modified the business organi- zation of enterprises and the way they do business. The efficient management of the new form of business needs new tools. Particularly, in supply networks, to solve production planning and scheduling problems, many researches have been widely conducted on heuristic algorithms, such as tabu search, simulated annealing algorithm, and genetic algorithm, but first and foremost, the genetic algorithm finds a near-optimal solution in a reasonable computation time when the prob- lem size is very large [see in: Dayou et al., 2009]. Therefore, this book presents an optimization method with genetic algorithms for operating decision making in new structures of business. Genetic algorithms are probabilistic search algorithms, which mimic bio- logical evolution to produce gradually better offspring solutions. Each solution to a given problem can be encoded by a string that represents an individual in a population. The population is evolved, over generations, to produce a better solution to the problem. The evolution of the genetic algorithm population from one generation to the next is usually achieved through the use of three operators that are fundamental: selection, crossover, and mutation. The process of repro- duction, evaluation, and selection is repeated until a termination criterion is reached. Holland [1975] first described a genetic algorithm, which is commonly called the classical genetic algorithm (CGA). This book focuses on both the theory and applications of genetic algo- rithms for planning and scheduling in supply networks. The theoretical side deals with the procedures of genetic algorithms, representation, selection and genetic operators. The purpose of this book is to pay special attention to applications of genetic algorithms to the supply network planning and scheduling. Thus, the ap- plications of genetic algorithms concern mainly production environments. 8 Introduction A huge amount of literature on planning and scheduling in supply net- works including the use of genetic algorithms has been published within the last years. Therefore, this book is divided into two parts. Part I (Chapters 1 to 2) pre- sents the general aspects of the supply network management, with background information on the planning and scheduling methods. Part II introduces to ge- netic algorithms and presents their applications. (cid:147)No business is an island(cid:148) [H(cid:229)kansson and Snehota, 1989]. Therefore, the main objective of studies presented in Part I is to analyze the concept and forms of inter-organizational cooperation from a viewpoint of the operating decision making. It is not the intention of this part to give a detailed description and an analysis of all problems of the supply network management but the survey in which the emphasis is placed on optimization problems, where advanced plan- ning and scheduling methods are needed. Thus, Chapter 1 of the book introduces the basics of supply network management starting with a definition of the supply network and coordination problems and characteristics of the types of produc- tion most commonly found are outlined. Chapter 2 describes the general struc- ture of advanced planning system (APS) and its modules. Finally, the main char- acteristics and development trends of the advanced planning and scheduling methods are presented. Part II introduces to genetic algorithms and provides a survey of the evo- lutionary-based methods for planning and scheduling and supply network con- figuration. The literature on the production planning in supply chain manage- ment systems is abundant. It is, however, impossible to provide an exhaustive review discussing every piece of work that has been done over the years. There- fore, the author has to arbitrarily select the most representative work known to them. As above mentioned, the third chapter of Part II introduces to genetic algo- rithms. This chapter focused mainly on procedures of genetic algorithms, selec- tion, and genetic operators. The main objective of the Chapter 4 is to present heuristic methods based on evolutionary algorithms to address the supply net- work configuration. The focus is brought on problems related to the design, or- ganization, and management of the supply network. In the literature, there is a variety of modeling techniques that potentially could be used to model supply chains. These approaches can be divided into two distinct categories according to the optimization of supply network configuration: the node of the supply net- work (e.g. cells, the factories) and the whole of the network (e.g. industrial clus- ters, global supply networks). In the node of the supply network, there are appli- cations of evolutionary algorithms in next problems: grouping parts and machines, facilities layout. The survey of the optimization of the whole supply network with evolutionary algorithms includes the plant layout problem. In Chapter 5 some concepts of the evolutionary-based methods for advanced planning and Introduction 9 scheduling are outlined. The overview is structured in the following way. First, genetic algorithms for solving planning problems are presented. Next, for better understanding of the key concepts of encoding and decoding in genetic algo- rithms, a brief survey of representation methods in scheduling problems is pre- sented. The overview of evolutionary-based methods for advanced scheduling categorizes the literature according to shop environments, including parallel ma- chines, flow shop, permutation flow shop, flexible flow shop, job shop, open shop, multi-factory system and others. As above mentioned, advances in intelli- gent methods have significantly modified the business organization of enter- prises and the way they do business. Therefore, Chapter 6 presents novel optimi- zation methods for operating decision making in new structures of business. The scope of this chapter is to propose a new optimization procedure combining ge- netic algorithms and other methods to solve distributed scheduling problems in manufacturing environments. Chapter 6 will not only concentrate on planning and scheduling, but it will also describe ideas of control in supply networks us- ing genetic algorithms. In this chapter, an experimental verification of the pro- posed genetic algorithms is also reported and representative examples are pro- vided to show that the suggested novel method can improve planning and sched- uling in supply networks. The production plans for experiments with genetic algorithms are included in the appendix. In adaptation of genetic algorithms to the planning and scheduling prob- lem, two issues have been considered. One is how to encode a solution of the problem into a chromosome so as to ensure that a chromosome will correspond to a feasible solution. The other issue is how to enhance the performance of ge- netic search. In this book placed is emphasis on encoding methods. Finally, a discussion on the current research status and most promising paths of future research is presented in last chapter. The author concludes that advances in genetic algorithms create new prospects for inter-organizational co- operation. This book will be a valuable source for managers and consultants alike, initiating and conducting projects aiming at introducing an Advanced Planning System industry. Also, students attending postgraduate courses in supply net- work management and related fields will profit from material provided. Part I BASICS OF THE SUPPLY NETWORK MANAGEMENT 1 Theoretical foundations of the production in network Supply network management (SNM) seems to be a growing area of interest amongst researchers and practitioners from varied disciplines. This chapter ex- plores two themes. First, identifies and describes the basic management issues involved in supply networks. Second, the planning and scheduling in production networks is discussed. In particular, this chapter defines concepts of supply net- work (SN) and supply network management, especially as regards supply net- work management such as coordination of inter-organizations(cid:146) decision making. 1.1. Definition of key terms Network can be defined in many ways. In generally, a network organiza- tion can be defined as an environment around which people organize themselves to attain a common objective [Sailer, 1978]. The notion of (cid:147)network(cid:148) is used to characterize any set of recurring ties (e.g. resource, friendship, information ties) among a set of nodes (e.g. individuals, groups, organizations, information sys- tems and so on) [Fombrun, 1982]. Santoro et al. [2006] state that network or- ganizations can be defined by structure, process, and purpose elements. Structurally, a network organization combines co-specialized assets under shared control. Procedurally, a network organization supports participants(cid:146) ac- tions via their roles and positions within the network organization. The literature incorporating structural holes generally examines relationships in terms of in- traorganizational networks [e.g. Bogenrieder and Nooteboom, 2004; Gargiulo and Benassi, 2000] or horizontal interorganizational alliances [e.g. Taylor and 14 I. Basics of the supply network management Doerfel, 2003]. Very few researchers have examined structural holes in the con- text of supply network relationships [Gassenheimer et al., 2007]. Therefore, the purpose of this study is the investigation of relationships between supply chain networks and activities, particularly from the viewpoint of planning and control. Besides, this chapter attempts to study the organizational differences between Small and Medium Scale Enterprises (SMEs) and a focal firm, arising out of differences in objectives, structures and operational activities. Partnership and relationship are a widely used typical terms for a certain development stage of companies’ cooperation. The difference between partner- ship and network relationship is the context of companies’ cooperation. Network relationship is a supply relation between companies taking part in a network and having one or more common objectives [Kulmala et al., 2002]. In the literature, many authors defined (cid:147)supply chain(cid:148) (SC) but few au- thors defined (cid:147)supply network(cid:148) (SN) although they considered the network. For example, Pibernik and Sucky [2007] defined the supply chain as follows: (cid:147)Sup- ply chains (SCs) can be considered as networks of different geographically dis- persed facilities ‒ where raw materials, intermediate and finished products are produced, tested, modified, and stored ‒ and the transportation links that connect the facilities. Similarly Lin and Lin [2006] define: (cid:147)A supply chain is a network of suppliers, factories, warehouses, distribution centers and retailers where the raw materials are acquired, manufactured to products, which then are delivered to consumers.(cid:148) Thus, SCs are interorganizational systems with a multiple num- ber of planning domains (e.g. organizational units within a firm, or individual companies such as manufacturers of finished goods, suppliers of intermediate products and logistics service providers), each responsible for a specific set of facilities or transportation links of the SC.(cid:148) Blackhurst et al. [2005] reported that (cid:147)Supply chains are interlinked networks of suppliers, manufacturers, distributors and customers that aim to provide a product or service to customers.(cid:148) In the net- work literature, there is also used the term (cid:147)supply chain network.(cid:148) For example, Pokharel [2008] defines: (cid:147)A supply chain network (SCN) refers to a number of entities such as the raw material suppliers, basic parts manufacturing units, com- ponent suppliers, inventory service providers, assemblers, distributors, retailers and customers. Each group of these entities, for example, all raw material sup- pliers, is called an echelon. The goal of SCN design is to obtain a network that satisfies the objectives set forth by the decision makers, for example, the choice of a network that minimizes the costs but maximizes the customer service level.(cid:148) Danilovic and Winroth [2005] claimed that the authors use the word network to describe both vertical and horizontal relations as well as possible combinations of them but the current trend has been to decrease the difference among these three terms (i.e. supply chain, supply network, supply chain network). 1. Theoretical foundations of the production in network 15 Stock et al. [2000] specify two constructs defining supply chain structure. The first is the geographic dispersion of the supply chain (cid:150) the geographic scope of the locations of the suppliers, production facilities, distributors, and customers in the supply chain. The second is the classification of how the firm(cid:146)s supply and distribution channel suppliers, production facilities, distributors, and customers, are governed (cid:150) as a network, hierarchy, or market. Geographic dispersion refers to the extent to which the elements in a firm(cid:146)s supply chain are located across a wide range of geographic regions. Thus, elements of the supply chain include suppliers, production facilities, distributors, and customers. Configurations of channel governance concern: networks, hierarchies, and markets. The supply chain is traditionally characterized by three types of flows [Akkermans et al., 2003]: (cid:150) material flows: which represent physical product flows from suppliers to customers as well as the reverse flows for product returns, servicing, and recycling; (cid:150) information flows: which represent order transmission and order tracking, and which coordinate the physical flows; and (cid:150) financial flows: which represent credit terms, payment schedules, and consignment and title ownership arrangements. Ballou et al. [2000] divide supply chain activities into three main areas: (1) intrafunctional coordination (administration of the activities and processes within the logistics function of a firm); (2) coordination of interfunctional activi- ties, such as between logistics and finance, logistics and production, and logis- tics and marketing, as they take place among the functional areas of the firm; and (3) coordination of interorganizational supply chain activities that take place between legally separate firms and their suppliers. This perspective reflects the concept of e-marketplace, in which supply chain activities span the organiza- tional boundary through upstream and downstream linkages, and the integration of supply chain activities extends beyond the product flow function within the same firm to external functional areas. M(cid:246)ller et al. [2005] contend that the managerial challenges of strategic nets are fundamentally influenced by the position of the specific net in the value- system continuum. From this viewpoint, they claim that most existing nets can be positioned in the following types: 1. Vertical value nets, including supplier nets, channel and customer nets and vertically integrated value systems. 2. Horizontal value nets, covering several modes: competition alliances; re- source/capability access alliances; resource and capability development alliances; market and channel access/cooperation alliances; (cid:147)networking forums(cid:148) ‒ company or institutionally driven. 16 I. Basics of the supply network management 3. Multidimensional value nets (MDVNs), including (cid:147)core or hollow organi- zations,(cid:148) complex business nets and new value-system nets. Thus, generally speaking, the network has a certain structure that consists of customers(cid:146) and their direct and indirect suppliers(cid:146) who possibly have supply relations with each other. Supply networks are defined as interlinked networks of suppliers, manufacturers, distributors and customers that aim to provide a product or service to customers [Blackhurst et al., 2005]. Network analysis begins with the assumption that all supply chain partners are embedded in multiple social relationships [Granovetter, 1985] and connected through a value-added linkage that provides a strategic advantage for the entire group [Burt, 2004]. Central to network theory is the positions of parties in relation to the rest of the network. For example, a supplier in a supply chain holds a nodal position and may act as a broker connecting different distributors in the network [Gassenheimer et al., 2007]. Firms are in various ways embedded in networks where both economic factors and social dimensions are crucial [Gadde et al., 2003]. Thus, various types of supply networks can be formed by different classes of firms to respond to new market challenges. Generally, based on the distance criterion between firms within a network, two types of supply networks may be recognized: the global one, and the local one. From the viewpoint of relationships, two basic structures of supply net- works may be recognized: the structure dominated by one enterprise and the supply network based on a partnership. Figure 1.1 illustrates overall structures of these two types of supply networks. Figure 1.1. Overall structures of supply networks S S FC SC C C (a) Model of structure dominated by focal factory where: FC ‒ focal factory, S (cid:150) supplier, C ‒ customer, SC ‒ subcontractor 1. Theoretical foundations of the production in network 17 F F F F F F (b) Model of supply network based on partnership where: F ‒ partnering firms Source: Ławrynowicz, 2011a. In the structure dominated by one enterprise (Fig. 1.1a) there are four types of enterprises: focal enterprise (i.e. dominant enterprise), delivery, cus- tomer, and subcontractor. The focal factory is a coordinator of processes of supply networks. Each focal organization has its own unique network that comprises a unique set of actors, resources, and activities, which together constitute its identity. A global supply chain setup normally incorporates a focal firm that pro- duces the main product, number of suppliers of raw materials and services, hun- dreds of distributors and dealers, and the end customers [Morya and Dwivedi, 2009]. Thus, the global supply network consists of many different organizational units with multiple tiers and can be very complex as shown in Figure 1.2. Figure 1.2 shows that a network usually will not only focus on a flow within a single chain, but usually will have to deal with different flows. The global supply network (GSN) with one dominant enterprise is also known as (cid:147)global supply chain,(cid:148) (cid:147)global factory(cid:148) [Buckley, 2009], (cid:147)multinational enter- prise(cid:148) [Buckley, 2009], or (cid:147)network enterprise(cid:148) [Castells, 2000]. A network en- terprise, defined by Castells [2000] is a specific form of enterprise whose system of means is constituted by the intersection of segments of autonomous systems of goals, spreads across firms that share each others resources, but whose goals are independent of each other. In other words, a global supply network is a world- wide network of suppliers, manufactures, warehouses, distribution centers and retailers through which raw materials are acquired, transformed and delivered to customers. 18 I. Basics of the supply network management Figure 1.2. Global supply network S S S S S S S S S SC FC C C C C C C C C C C C C Small and Medium Scale Enterprises (SMEs) are an important part of any supply chain in any industry but their role is nonetheless very restricted in a global supply network by the focal factory. Therefore, SMEs create local supply networks based on partnership which are also known as (cid:147)clusters.(cid:148) In the recent economic and geographical literature, the phenomenon of local industrial clus- ters has attracted much attention, and the term (cid:147)cluster(cid:148) is widely used like the note (cid:147)industrial cluster,(cid:148) (cid:147)industrial districts,(cid:148) (cid:147)industrial local clusters,(cid:148) (cid:147)inno- vative milieu(cid:148) and (cid:147)regional innovative systems(cid:148) [see in: Brenner and Gildne, 2006]. For example, Carbonara et al. [2002] describe industrial districts, which could be characterized as a number of supply chains, each built up of small and medium-sized companies that are linked together through a complex network structure. Geographical clusters are highly complex entities configured in many dif- ferent ways. Studies carried out on this topic have generated a large number of definitions to identify the geographical clusters. Each of them stresses different and complementary aspects characterising geographical clusters. For example, Porter [1998] defines a cluster as a geographically proximate group of intercon- nected companies and associated institutions (for example, universities, stan- dards agencies, and trade associations) in particular fields, linked by commonal- ities and complementarities (they compete but also cooperate). Similarly, Navickas 1. Theoretical foundations of the production in network 19 and MalakauskaitØ [2009] defined clusters as geographically integrated compa- nies and associated organizations that share together technological know-how, knowledge, skills, competencies, and resources. Niu [2009] defined the notion industrial cluster (IC) as (cid:147)a geographical and sectoral concentration and combi- nation of firms.(cid:148) Thus, industrial or business clusters are based on the physical proximity of firms in one area or region. Clusters (and similar forms of inter- -organizational structures) create an environment for innovation and technologi- cal advancement. Therefore, SMEs may gain additional benefits that include know- -how, cost-saving options, innovative solutions, etc. [Navickas and Malakaus- kaitØ, 2009]. Analysing the definitions presented in the literature on geographical clus- ters, Carbonara [2005] identifies some key common features characterizing this specific production model, namely: (cid:150) the geographical proximity of small and medium sized firms, (cid:150) a dense network of inter-firm relationships, in which the firms cooperate and compete at the same time, (cid:150) a dense network of social relationships, based mainly on face-to-face con- tact, which is strictly inter-connected with the system of economic rela- tionships, (cid:150) the presence within the area of complementary competencies and skills, (cid:150) a high degree of specialisation of both the firms and the workforce. From the viewpoint of manufacturing, in many cases, the industrial cluster is a distributed manufacturing system (see: Figure 1.1b). In the industrial cluster, the individual operating decision making is dependent on the resources of the other factories, and the possibilities of the individual organization to utilize these resources are determined by their place in the network. To summarize, the study places emphasis on the following differences of supply network structures. The structure dominated by one enterprise is a char- acteristic of the global supply network. A global supply network is usually char- acterized by a long time of transport operations, large number of tasks, and large size of operations. Therefore, it is not possible to create one common system for job shop scheduling in the global supply network. In this network, each node (i.e. enterprise) applies an autonomous method for operations management, and detailed production scheduling is performed individually for each plant. A local supply network is usually based on partnership. In the industrial cluster, there are transport operations with a relatively short time, smaller number of tasks, and a relatively smaller number of operations. In this supply network, the operations management and scheduling can be executed together. 20 I. Basics of the supply network management 1.2. Supply network management From the global viewpoint, supply network management (SNM) is the process of planning, implementing and controlling the efficient, effective flow and storage of goods, services and related information from one or more points of origin to the points of production, distribution and consumption in order to meet customers(cid:146) requirements on a worldwide scale [see in: Edwards and Shar- man, 2000]. It is the process of integrating the existing business activities along the value chains, where more suppliers of some raw materials or more production cells of some semi-products can appear in order to create value for the end user. The main drivers of globalization have been [Bogataj M. and Bogataj L., 2004]: (cid:150) the decreasing tariffs (WTO, GATT), (cid:150) the improvement of transportation efficiency (the emergence of air travel, faster ocean crossings, etc.), (cid:150) rapid development of communication and information technology. Supply network management helps firms in integrating their business by collaborating with other partners to meet the unpredictable demand of the end user. Several authors recognise that integration is a fundamental principle of SNM. For example, Lambert et al. [1998] defined supply chain management (SCM) as follows, (cid:147)supply chain management is the integration of key business processes from end user through original suppliers that provides products, ser- vices, and information that add value for customers and other stakeholders.(cid:148) But generally, most authors noted that coordination and integration mechanisms are the key dimensions characterizing SNM. Cooke [1997], for example, defines SCM as (cid:145)(cid:145)successful coordination and integration of all those activities associ- ated with moving goods from the raw materials stage through to the end user, for sustainable competitive advantage. This includes activities like systems man- agement, sourcing and procurement, production scheduling, order processing, in- ventory management, transportation, warehousing, and customer service(cid:146). Simi- larly, Lee and Ng [1997] maintain that the distinction between SNM and tradi- tional operations management lies in two dimensions of flow coordination and organisational integration. Malone [1987] defines coordination as a pattern of decision making and communication among a set of actors who perform tasks to achieve goals. A coordination mechanism consists of (1) the informational struc- ture defining who obtains what information from the environment, how that in- formation is processed and then distributed among different members participat- ing in the mechanism itself, and (2) the decision-making process helping to se- lect the appropriate action that need to be performed from the set of alternative solutions [Marschak and Radner, 1972]. Hewitt [1994] maintains that supply 1. Theoretical foundations of the production in network 21 network co-ordination relates to planning, monitoring and aligning intra- and interorganisational logistics processes, because such processes can be considered as the vehicle of materials, information and financial flows across the supply net- work. Arshinder, et al. [2008] stated that the terms like integration, collaboration, cooperation and coordination are complementary to each other and when used in the context of supply chain can easily be considered as a part of supply chain coordination. This assumption can be followed without loss of generality as the elements like integration (combining to an integral whole), collaboration (work- ing jointly) and cooperation (joint operation) are the elements of coordination. In the definition of SNM, emphasis is placed not only on coordination but strategic and long term aspects. For example, [Sch(cid:246)nsleben, 2003] defined sup- ply chain management as (cid:147)the coordination of a strategic and long-term coopera- tion among co-makers in the global logistics network for the development and production of products, both in production and procurement and in product and process innovation.(cid:148) As well, Li et al. [2005], noticed that SCM has been de- fined to explicitly recognize the strategic nature of coordination between trading partners and to explain the dual purpose of SCM: to improve the performance of an individual organization, and to improve the performance of the entire supply chain. Different coordination models have been proposed considering isolated activities or different functions of supply network. Various coordination mecha- nisms suggested in these models help in improving the various performance measures of the supply chain. Arshinder et al. [2008] specify four main types of coordination mechanisms: (cid:150) contract, (cid:150) information technology, (cid:150) information sharing, (cid:150) joint decision making. Members of supply network coordinate by using contracts for better man- agement of supplier ‒ buyer relationship and risk management. The contracts specify the parameters (e.g. like quantity, price, time and quality) within which a buyer places orders and a supplier fulfills them. The objectives of SN contracts are: to increase the total SN profit, to reduce overstock/understock costs and to share the risks among the SN partners. IT is used to improve inter-organizational coordination [McAfee, 2002; Sanders, 2008] and in turn, inter-organizational coordination has been shown to have a positive impact on selecting firm per- formance measures, such as customer service, lead time and production costs. Advances in IT e.g. internet, EDI (electronic data interchange), ERP (enterprise resource planning), e-business, (and many more) enable firms to rapidly exchange products, information, and funds and utilize collaborative methods to optimize
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Genetic algorithms for advanced planning and scheduling in supply networks
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