Developing Agile Supply Chains–system model, algorithms, applications

Developing Agile Supply Chains – system model, algorithms, applications Katarzyna Grzybowska1, and Gábor Kovács2 1

Poznan University of Technology, Faculty of Engineering Management, Chair of Production Engineering and Logistics, Strzelecka 11, 60-965 Poznan, Poland [email protected] 2 Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Department of Transportation Technology, Műegyetem rkp 3, 1111 Budapest, Hungary [email protected]

Abstract. Nowadays, a modern company operates as a network of companies, not as a single company. These companies are called virtual enterprises, whose main purpose is the maximal fulfilment of costumer needs. Based on this, the paper presents the construction of agile supply chains and as an example it details the model, the algorithms and the applications of a modern electronic freight and warehouse exchange, which is a type of virtual enterprises. Keywords: agile, supply chain, e-commerce, optimization, decision supporting.

1. Introduction The interest in the concept of Supply Chain (SC) results from the engagement of theoreticians and practical researchers in the integrated flow of goods from the supplier to the end client on an increasingly turbulent, unpredictable market. It is in the 1980s that organizational solutions and the general concept of Supply Chain Management (SCM) became an alternative to the traditional (usually transactional) manner in which the relationship is perceived and the manner in which a business operates between cooperating suppliers and recipients. The SC is a network of organizations that are involved in different processes and activities that produce value in the form of products and services in the hands of the ultimate consumer [1]. The Supply Chain is a metastructure [2]. There can be distinguished constitutive elements (characteristics) of the supply chains. These constitutive elements allowing for the identification of the supply chains that differ considerably [3]: (1) supply chain size, (2) the ascribed roles of supply chain participants, (3) status of participants of a supply chain, (4) coherence of the supply chain, (5) communication in a supply chain, (6) interactions within a supply chain.

adfa, p. 1, 2011. © Springer-Verlag Berlin Heidelberg 2011

The Supply Chains are longer, more dynamic and riskier. They are much more complex. A metastructure is characterized by a dynamic holarchy of cooperating holons (commercial entities) and holonic system (HS). The greater the supply chain grows, the less coherent and lacking close relationships are. In turn, this results in a situation in which in such a metastructure’s connections and dependencies may vary in permanence. One differentiates permanent links (the socalled core supply chain) and dynamic ones which change depending on the task carried out (the so-called temporary links). After cooperation is concluded, the temporary links become disconnected from the supply chain cooperation. The SC is a concept designed to manage entire supply chains consisting of numerous participating organizations [4]. SCM is based on the understanding that the challenges of the present-day competition cannot be effectively faced through isolated changes in the individual companies but through the development of collaboration between the participants in the production and the delivery of products from the initial sources to the end customers [5]. New market and economy need the Agile Supply Chain (ASC). The ASC must possess several distinguishing characteristics as Fig. 1 suggests [6]: the ASC (1) is market sensitive; (2) uses information technology to share data between buyers and suppliers, in effect, creating a virtual supply chain; (3) is integrated – the share of information between supply chain partners (collaborative working between buyers and suppliers, joint product development, common systems and shared information; “extended enterprise” as it is often called, there can be no boundaries and an ethos of trust and commitment must prevail); (4) is a confederation of partners linked together as a network.

Fig. 1. The Agile Supply Chain [9]

The techniques of information sharing (i.e., information centralization) can be supported by information technologies such as e-Hubs [7]. The basis of these information technologies is currently the Internet and the application of multiagent systems in SC. Intelligent agents are a new paradigm of software system development. Nowadays, it seems that researchers agree on the following definition proposed by Wooldridge and Jennings [8]. The term “agent” denotes a hardware or (more usually) software-based computer system, that has the following characteristics: (1) Autonomy: agents operate without the direct intervention of humans or others, and has some kind of control over

its actions and internal state; (2) Social ability: agents interact with other agents (and possibly humans) via some kind of agent-communication language; (3) Reactivity: agents perceive their environment, (which may be the physical world, an user, a collection of other agents, the Internet, or perhaps all of these combined), and respond in a timely fashion to changes that occur in it; (4) Pro-activeness: agents do not simply act in response to their environment, they are able to exhibit goal-directed behaviour by taking the initiative [9]. Agility in the Supply Chain is the ability of the supply chain as a whole and its members to align rapidly the network and its operations to the dynamic and turbulent requirements of the customers. The main focus is on running business in network structures with an adequate level of agility to respond to changes as well as proactively anticipate changes and seek new emerging opportunities [10]. They should be able to be flexible, responsive and adaptable to changing market conditions. This can be achieved through collaborative relationship, process integration, information integration, and customer/marketing sensitivity achieving customer satisfied objectives. The SC is agile and responsive in an increasingly competitive and fast-paced business world, when has informational nervous systems that extend beyond their own corporate boundaries (Fig. 2).

Fig. 2. Informational nervous systems in Single Enterprise and Agile Network [11]

2. Developing Agile Supply Chains - four stages of Supply Chain integration according to Stevens Stevens identified four stages of SC integration and discussed the planning and operating implications of each stage [14]: (Stage 1) Represents the base line case. The SC is a function of fragmented operations within the individual company and is characterized by staged inventories, independent and incompatible control systems and procedures, and functional segregation; (Stage 2) Begins to focus internal integration, characterized by an emphasis on cost reduction rather than performance improvement, buffer inventory, initial evaluations of internal trade-offs, and reactive customer service; (Stage 3) Reaches toward internal corporate integration and characterized by full visibility of purchasing through distribution, medium-term planning, tactical rather

than strategic focus, emphasis on efficiency, extended use of electronics support for linkages, and a continued reactive approach to customers; (Stage 4) Achieves SC integration by extending the scope of integration outside the company to embrace suppliers and customers.

3. Developing Agile Supply Chains - three stages of ASC The development of the SC takes place in three main stages, in which a total of seven phases may be differentiated [15]:  Stage 1: Strengthening the contact  Stage 2: Maintaining the contact  Stage 3: Loosening the contact The first step in strengthening an enterprise’s business contacts is the initiation of the contact. In this phase, the selection of the business partner takes place along with the initial assessment of the possible terms and conditions of cooperation. Coordination mechanisms are also started up. The performance of a supply chain depends critically on how its members coordinate their decisions. Sharing information is the most basic form of coordination in Supply Chains. Further positive business relations lead to integration among enterprises. To a large extent, this phase is based on the creation of a certain cooperative of interests. In the contract maintenance phase – the integration phase – the following may be observed: (1) increased communication; (2) greater readiness to cooperate; (3) an increased plan for the actions of others; (4) the more effective achievement of the intended objectives; (5) an increased level of satisfaction in cooperation. In this integrated phase, the enterprises also expect more from each other. The integration phase ends if the enterprises do not overcome the crisis periods. The limiting business contacts phase begins. The result of the extending limitation of the business relations is the impasse.

4. Agile Supply Chains – model of electronic freight and warehouse exchanges With the help of the Internet, information can be sent to participants of business processes in the fraction of a second, which, by accelerating and optimizing these processes, facilitates an easy overview and comparison of supply and demand [16], [17]. For this reason, electronic marketplaces have emerged in numerous fields, such as freight exchanges in the field of carrier services. Freight exchanges create a meeting point for freighters and consigners. Consigners can advertise their freight tasks for shipment in the catalogue of the marketplace; similarly, freighters can make their bid for cargo holds. Moreover, the users of these exchanges can choose the most suitable

offer by using different search algorithms. Warehouse exchanges sell free warehouse space/task either with a simple advertisement or by using search functions. Nevertheless, because underdeveloped transactional solutions set back the development of such exchange types. The overall structure of freight and warehouse exchanges is supplemented by showing other modules and services, too, in the forthcoming subsections. These could be important and useful modules in the future. The developed freight and warehouse exchange offers the following main services [18]: e-commerce toolbar; multi-criteria decision supporting algorithms (choose the best offer); optimization algorithms (optimize the logistics processes); other functions (e.g. statistics, blacklists, data maintenance, etc.). The aims of the electronic freight and warehouse exchange: to advertise freight/storage capacities/tasks; to choose suitable offers based on e-commerce methods and complex optimum criteria [19]; to support complex logistic processes (e.g. combined transport, city logistics, etc.). When a new customer who has not used the system before wants to register, their personal data and contact details must be entered. Also, we can specify here the filtering criteria which are necessary for the automatic offer sending, and we can also add our personal negative experiences. Consigners specify the details of their freight/storage tasks (e.g. temporal/spatial/physical parameters, etc.). Logistics providers can do a search based on the mentioned parameters. It is also possible to find backhaul and to look at the whole task offer here, too. Logistics providers can offer their freight/storage capacities by displaying all relevant information (e.g. temporal/spatial/physical parameters, etc.). Consigners can do a search based on the mentioned parameters. We can take a look at the whole capacities offer here, too. After giving our personal data, the system allows us to enter filtering criteria which will help us to choose quickly from the latest offers (automatic offer sending.). Such criteria are: time, spatial or physical limitations, etc. There is opportunity to have a freight/storage commission through tender or auction [20], [21]. Experiences show that tenders for high-value, long-term and repetitive freight/storage tasks are worth advertising on the electronic freight and warehouse exchange.

5. Agile Supply Chains - decision supporting One of the chief values of the developed electronic freight and warehouse system is the automatic application of multi-criteria evaluation methods that are well-known from books, but may not be used enough in practice. The developed mathematical method (MDA: Multi-criteria Decision supporting Algorithm) helps to evaluate tenders/auctions [22]. MDA is based on the principle of the AHP - Analytic Hierarchy Process - [23], [24], and other methods (e.g. caeteris paribus, mathematical maximal sensitivity analysis). MDA is an MS Excel and VBA-based (Visual Basic Application) application. By its decision making nature, it generates reports (Table 1.) that help making wellfounded and agile decisions. The main goal:

Weighted performance value => MAX!

(1)

Table 1. MDA generated report in the course of a freight tender (example) Main aspects Name Fare (100 Euro)

Sub aspects

Offers and their values

Weight

Name

Weight

Interpretation

1

2

3

4

5

Ideal

0.4082

Fare (100 Euro)

1

lower

421

525

590

586

448

421

Deadline (day)

0.2041

Deadline (day)

1

lower

3

3

4

2

3

2

Proximity

0.1361

Proximity

1

higher

0.3457

0.3457

0.1728

0.0494

0.0864

0.3457

Services

0.102

Services

1

higher

0.125

0.25

0.125

0.25

0.25

0.25

Information connections

0.068

Information connections

1

higher

0.1509

0.2264

0.4528

0.0566

0.1132

0.4528

References

0.0816

General references

0.75

higher

0.2759

0.1379

0.1379

0.2759

0.1724

0.2759

Trust

0.25

higher

0.1429

0.2857

0.2857

0.1429

0.1429

0.2857

Sensitivity Fare (100 Euro)

14.59%

1

0.8015

0.7127

0.7186

0.9393

1

Deadline (day)

4.93%

0.6667

0.6667

0.5

1

0.6667

1

Proximity

3.33%

1

1

0.5

0.1429

0.25

1

Services

4.48%

0.5

1

0.5

1

1

1

Information connections

4.35%

0.3333

0.5

1

0,125

0.25

1

References

0.53%

0.875

0.625

0.625

0.875

0.5938

0.875

1

2

3

4

5

0.8254

0.863

0.631

0.6988

0.721

1

2

5

4

3

0.8254

0.7863

0.721

0.6988

0.631

Offers Weighted value

performance

Offers Final order of offers

Weighted value

performance

6. Agile Supply Chains - optimization algorithms and applications: agile combined transportation system The basic function of electronic freight and warehouse exchanges is to establish connection between free freight and storage capacities and tasks. In the database of such online fairs there is high number of freight and storage capacity offers and tasks, which provides good optimization opportunity for logistics providers [25]. In the freight exchange the optimum search task may be formulated on the basis of the following objective function: those having free freight capacity wish to establish routes providing optimal profit from the freight tasks appearing in the freight exchange. Many freight tasks may be included into the route, but a new freight task may

be commenced only after the completion of the previous one. The objective function is to reach the maximum profit. In the warehouse exchange those having free storage capacity wish to choose several from the available storage tasks by setting the goal of ideal exploitation of capacity. In case of freight and warehouse exchanges, we have to define a complex objective function. On a part of the total transport route, the freight tasks are transmitted together and then with the help of a combi terminal the freight tasks are transferred (multimodal transportation with rail/river, BA_ACO algorithm, Fig. 3).

Fig. 3. Multimodal transport supported by freight and warehouse exchange: the model layout and the ant colony algorithm (BA_ACO)

The objective functions (maximum benefit, H, see equation (2)): 1. maximal use (KCF) of the rail/river vehicle, 2. maximal total mileage reduction (FCF, kilometre), 3. minimal transportation performance increase (QCF, ton*kilometre), 4. optimal demand of the surplus logistic services (RIBF). H=RIBF.KCF.FCF/QCF=>MAX!

(2)

This problem can be solved by ACO (ant colony optimization), which is an optimizing algorithm developed by Marco Dorigo [26] based on the modeling of the ants’ social behavior. In nature ants search for food by chance, then if they find some, on their way back to the ant-hill they mark the way with pheromone. Other ants – due to the pheromone sign – choose the marked way with higher probability instead of acci-

dental wandering. Shorter ways may be completed quicker, thus on these ways more pheromone will be present than on longer ones. After a while the amount of pheromone drops (evaporation), by this preventing sticking to local optimum. In the electronic freight and warehouse exchange similar problem emerges as the ants’ search for food: the target is the agile performance of freight/storage tasks offering the higher profit. There are some researches in this topic [27], [28], [29]. The ant colony algorithm usable in electronic freight and warehouse exchanges (BA_ACO) operates upon the following large-scale procedure (Fig. 3, [29]):  Definition of input data: ─ starting point of optimum search (e.g. combi terminals, etc.), ─ narrowing down search space (local search): e.g. the selection of performable freight tasks depending on the distance compared to the combi terminals, ─ collection of the main features of the combined/non combined transport (mileage, transportation performance), ─ establishment of pheromone vector (the strength of the selection of freight tasks), ─ settling of profit vector (how much profit the selection of freight tasks will bring from the aspect of the route/solution).  Calculation of task selection probability: ─ the probability that a freight task will be fulfil through combined transport (based on e.g. pheromone, quantity, distance, etc.), ─ a vector may be formed from the above-mentioned probabilities (probability vector).  Establishment of solution possibilities: ─ establishment of random numbers, then selection of freight tasks upon probability vector, until the realization of the limiting conditions (e.g. capacity of train), ─ definition of the main features of the route (objective function parameters, equation (2)), ─ execution of the above-mentioned tasks in accordance with the number of ant colonies (e.g. ten ants = ten versions).  Evaluation of the results of the iteration step: ─ filling in the profit vector: freight tasks by freight tasks, choosing the highest profit in aspect of the total route/solution and set it in to the current freight task, then updating the maximum profit reached in the iteration steps, if improvement was realized, ─ updating the pheromone vector (based on e.g. reached profit).  Making new and new iteration steps (as long as further improvement cannot be reached, or after certain number of steps). The algorithm (BA_ACO) was coded and tested in MS Visual Basic language, as well as formulas and its characteristics. In the course of checkout there have been executed lot of runs (see Fig. 4: box plot chart helps to evaluate the parameters of program /BA_ACO/ and the results). Based on this, we can change for example the number of solutions (ants), iterations or runs.

Fig. 4. Box plot (the changes of benefit; 10 ants /10 solution versions/, 40 runs, 50 iterations)

7. Conclusion With the help of the presented methods, by the filtering of local optimums, an agile solution can be found shortly, which to freight/storage capacities/tasks selects freight/storage capacities/tasks. Through the coordination we are able to establish e.g. collecting-distributing routes, to organize back haul, and through this to reduce the number of vehicles. In this way, support of complex logistics processes will be possible (further research opportunities are based on e.g. [30]). In other words, freight and warehouse exchanges are one of the “simplest”, but still the most efficient way of optimizing complex logistics processes and developing agile supply chains.

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