Using empirical demand data and common random numbers in an agent-based simulation of a distribution network

Applications of agent-based modelling and simulation in the agri-food supply chains

Supply chain simulation is a fundamental approach for supply chain prediction, management, evaluation, and improvement. In order to simulate member behavior, organizational strategy, and management strategy of the supply chain, an agent-based modeling and simulation approach on multi-stage supply chain operation was proposed in this paper. First, the model structure of multi-stage supply chain operation was introduced. Then, the individual agent behavior model was emphatically studied, and hierarchical colored Petri-nets were used to describe the agent behavior process and cooperative behavior process. Finally, the model was validated using a series of simulation which focused on the agent inventory strategy.

PurposeThis work aims to measure the performance of an electric motors supply chain (SC) by using the Triple E performance measurement model to assess three performance dimensions simultaneously: efficiency, efficacy and environmental impact.Design/methodology/approachThis research presents a real case of a Brazilian company as an example for applying the Triple E performance measurement model and the discrete-event simulation to assess the performance of an SC.FindingsPerformance measurements for the three dimensions were the following: (1) for efficiency, a high inventory cost in the SC, driven by the distribution center (DC) (49.7% total cost); an order cycle time operating with an average of 21.7 days and a logistic channel transport capacity of 88%; (2) for efficacy, a service level of 98% for all channels; (3) for environmental impact, the SC emits a total of 395,733 kg of CO2 annually, with the DC and the regional distribution center (RDC2) being the largest emitters.Originality/valueThis work allowed to measure the performance of an SC interface (manufacturing process, a DC and three regional distribution centers). It was possible to measure the inventory holding cost and out-of-stock inventory costs, order cycle time, SC service level, transport capacity utilization and CO2 emissions in the transportation process of each SC stage and the whole SC. This study can be used as a decision support guide for academics and practitioners to measure and improve the SC performance.

Retailers must routinely contend with difficulties in managing the supply of their products due to disruptions in the supply chain. For new retailers, the challenge is how to design a resilient supply chain network; for existing retailers, the challenge is to adapt the supply chain network to satisfy customer demands. Generally, global retailers set up retail outlets in different areas to support specific customer zones and distribution centers (DCs) to manage the inventory for a cluster of retail shops. The supply chain network is usually highly exposed to external uncertainties like human-made and natural disasters. Therefore, disruptions to any of the supply chain nodes may result in the disconnection of the network and, ultimately, an interruption in the regular operations of the retailer. In this chapter, we consider an extended four-echelon centralized supply chain (CSC) consisting of the following echelons: (I) raw-materials suppliers, (II) manufacturers, (III) DCs, and (IV) retailers and their customer zones. We consider the retail business organization as the key stakeholder in this supply chain, as it owns the commercial outlets and the DCs, in addition to centrally controlling the supply operations of the four echelons. In developing our CSC, we review several resilience strategies that can be used to design or redesign a resilient retail supply chain. In doing so, we present the definition, advantages, and shortcomings of each strategy in the surveyed literature, and we also review the models that have been developed utilizing these strategies. Finally, we propose additional resilience strategies that can be adopted to improve supply chain operations when faced with major events or uncertainties, such as the disruptions caused by the COVID-19 pandemic.

PT Asagri Selaras Asia is an agribusiness company in Jakarta, Indonesia that provides food supply for entrepreneurs in the tourism sector, such as hotels and restaurants. In running their business, the company has a supply chain network that effectively integrates suppliers, manufacturers, warehouses, and stores. Supply chain management optimization is deemed necessary to maximize efficiency in every process carried out at PT Asagri Selaras Asia. One of the processes that can be optimized is the determination of facility location. The right facility location can minimize distance, delivery time, and operational costs and optimize the company's profit. Currently, the contract period for the distribution center (DC) used by PT Asagri Selaras Asia is about to expire therefore a decision is needed regarding the determination of the DC location for the next period, either extending the current DC contract or moving to a new location. This study aims to maximize the company's profit by comparing the profit obtained under existing and alternative DC, and the proposed DC from the experimental results using the Green Field Analysis (GFA) method. This study also aims to determine the feasibility of the three DC locations using the Network Optimization (NO) method with Anylogistix software. Based on the data analysis, the new DC is recommended to be located in the West Pejaten area, South Jakarta with latitude -6.2729150574 and longitude 106.8230798418 which will give an increase in profit of 80.53% compared to the existing DC.

Location-allocation problem as one of the strategic decisions in supply chain management has become the focus of research attention. In this paper we design a distribution network by modelling for location-allocation in a supply chain that involves a fixed plant, distribution centres with multiple levels of capacities and retailers. The aim is to select the optimum numbers, locations, capacities of the opening warehouses, allocation retailers to the opened warehouses, therefore all multi-product stochastic customer demands are satisfied at the minimum total cost of the distribution network and the maximum average of warehouse utilisation. In addition lateral transshipment within an inventory system is considered (i.e., product movements between locations of the same echelon). The model developed as a mixed-integer nonlinear programming model and an efficient heuristic-based memetic algorithm is proposed. Furthermore, a number of test problems are solved and the associated results are compared to evaluate the performance of the proposed algorithm.

전자상거래의 발전과 함께 물류유통을 위한 분배망의 구성은 점차 복잡해지고 있으며, 이에 따라 분배계획이 점차 중요해지고 있다. 분배계획에 있어서 분배망의 관리는 중요하다. 분배망은 분배센터(DC)와 그 상호작용으로 나타낼 수 있다. DC 내부요인 및 DC의 상호작용으로 인한 외부요인은 분배망에 많은 영향을 미친다. 따라서 효율적인 분배망 관리계획의 수립을 위해서는 DC와 DC의 상호작용을 고려한 분배망의 분석이 필요하다. 지금까지 자원할당 같은 공급망 관리 관점의 연구가 이루어졌지만 공급망을 구성하는 분배망의 분석에 대한 연구가 이루어지지 않았다. 본 논문은 DC와 DC의 상호작용을 고려한 분배망 분석 기법을 제안한다. 제안 기법은 크게 두 가지 단계로 이루어진다. 먼저, 분배망은 DC와 DC의 상호작용을 포함한 그래프 형태로 모델링된다. 두 번째, 그래프로 모델링된 분배망은 도달성 트리를 이용하여 분석된다. 또한 예제모델을 제시하고, 이것의 분석을 통해 제안기법의 효용성을 보였다. As development of the e-commerce, the distributing network for a logistics currency is more complicated. A management of the distributing network (DN) is important factor in distribution planning. The DN can be expressed to distribution center (DC) and the interaction of DC. An internal factor of DC and an external factor to occur by an interaction of DC have many influences on the DN. Therefore, for an efficient DN management plan, analysis of the DN that considered DC and an interaction of DC is required. Until now a study on a viewpoint of supply chain management as resources assignment was performed, but the study on analysis of the distribution network was not performed. This paper propose the distribution network analysis technique that considered DC and an interaction of DC. A proposed technique consists of two steps largely. First of all a DN is expressed with the graph that included an interaction of DC and DC. It uses a reachibility tree, and the following, a DN expressed with a graph is analyzed. Also we presented an example model, and show an usefulness of proposal technique with the analysis of this model.

Several studies have both qualitatively and quantitatively addressed the ‘buyer–supplier’ relationship; however, most of them have emphasized the two-echelon system. This study focuses specifically on the decisions of economic order quantity, shipment sizes, and number of shipments made under a three-echelon supply chain among manufacturer, distribution centre (DC), and retailer. The authors develop a two-integrated model (TIM) and, accordingly, we focus on the linkage of the two integrated models in the supply chain. From the results of this study, it is found that while the retailer becomes the focal company in the supply chain, the DC's loss tend to be the largest. However, if all parties in a supply chain agree to collaborate, and follow the joint optimal shipment size, the total relevant cost within the supply chain can be significantly reduced compared with typical delivery policy.

The supply chain design problem is one of the important problems in supply chain management. In this problem, the goal is to locate several facilities for distribution centers in different geographical areas to cover customer demands. In the model presented in this paper, customer demand is met through distribution centers, while these distribution centers supply products from manufacturing plants. In this paper, a mathematical model of integer linear programming is presented that, in addition to the optimal supply chain network design, considers the facility's location. This model aims to minimize the costs of sending products from the factory to distribution centers, from distribution centers to customers, and establishing distribution centers. To evaluate the proposed model, different network samples were created randomly on small, medium and large scales for experiments. In order to perform the experiments, a linear programming solver (LP Solver) and an iterated local search algorithm were used to compare the performance of each of these methods to find the optimal solution. These experiments show the superiority of the iterated local search algorithm compared to LP Solver in achieving the optimal solution in the shortest runtime for all instances.

This paper considers a single-sourcing network design problem for a three-level supply chain. For the first time, a novel mathematical model is presented considering risk-pooling, the inventory existence at distribution centers (DCs) under demand uncertainty, the existence of several alternatives to transport the product between facilities, and routing of vehicles from distribution centers to customer in a stochastic supply chain system, simultaneously. This problem is formulated as a bi-objective stochastic mixed-integer nonlinear programming model. The aim of this model is to determine the number of located distribution centers, their locations, and capacity levels, and allocating customers to distribution centers and distribution centers to suppliers. It also determines the inventory control decisions on the amount of ordered products and the amount of safety stocks at each opened DC, selecting a type of vehicle for transportation. Moreover, it determines routing decisions, such as determination of vehicles' routes starting from an opened distribution center to serve its allocated customers and returning to that distribution center. All are done in a way that the total system cost and the total transportation time are minimized. The Lingo software is used to solve the presented model. The computational results are illustrated in this paper.

Logistics system is a complex socio-economic system, and its core is the whole enterprise logistics integration, which includes the integration of the basic processes and objects, information integration of the supply chain, and the business integration of logistics business. In this paper the supply chain management is regarded as a breakthrough point, and on the basis of the research on current supply chain simulation, agent-based supply chain simulation is introduced. In this paper, the agent-based supply chain simulation modeling and realizing method is systematically researched. And the experimental results show that the simulation method is effective and advanced, and it is very effective to solve many problems of supply chain and achieve supply chain optimization, which can generate huge economic benefits for the businesses and the community.

Supply chain management is one of the new approaches that are considered significantly by variety of experts and enterprises in today competitive world. Supply chain refers to the network of facilities, supply centers, production centers and distribution centers which encompass various tasks such as providing raw materials, transforming raw materials to components or finished products and distributing them among customers. Regarding this issue, studying literature indicates on this fact that multi-level, multi-product, multi-period models in multi-sourcing situation by considering the supply capacity have not been taken into account notably and just few mathematical models are proposed for the analysis of such decisions. In this paper, it is attempted to investigate and delve into the supply chain planning issue in multi-level, multi-product, multi-period situation. In the proposed model, simultaneously optimization of two objectives is considered which entails maximizing the service level related to giving agreeable services to customers at each retailer's site and minimizing the overall costs of supply chain. As the proposed mixed integer non-linear model has specific complexity, branch and bound solver is utilized and has been applied for a data set in an automotive supply chain. In this way, a model has been presented which determines the lot size of ordering among various members in a supply chain, the amount of holding inventory at each elements of supply chain's site, optimal combination of selecting potential suppliers and the amount of ordering components to suppliers.

A large number of firms have reconfigured their supply chains. The general trends entail, among others, the reduction, centralization and re‐location of plants and distribution centers, the design of new distribution systems, and the reduction of the supplier base. The analysis of the implications of such reconfiguration for freight transport has received comparatively little attention, and most of the analysis has focused on the development of different theoretical models showing how changes in logistic structures and decisions could affect the transport demand. Using empirical data from Denmark, this paper sheds some light on the implications of reconfiguration supply chains on transport. Industry mail surveys among Danish firms as well as an in‐depth case study were performed. The consequences of the reconfiguration process on the present and future demand for transport are measured and analyzed in terms of the quantity of transport units used (trucks/containers), and the transport‐work (ton/km).

In recent years, many developments in logistics were connected to the need for information in an efficient supply chain flow. The supply chain is often represented as a network called a supply chain network (SCN) that is comprised of nodes that represent facilities (suppliers, plants, distribution centers and customers). Arcs connect these nodes along with the production flow. A multistage SCN (MSCN) is a sequence of multiple SCN stages. The flow can only be transferred between two consecutive stages. The MSCN problem involves the choice of facilities (plants and distribution centers) to be opened and the distribution network design must satisfy the demand with minimum cost. In this paper, a revised mathematical model is first proposed to correct the fatal error appearing in the existing models. An efficient hybrid heuristic algorithm (HHA) was developed by combining a greedy method (GM), the linear programming technique (LP) and three local search methods (LSMs) (always used in solving the scheduling problem). The pair-wise exchange procedure (XP), the insert procedure (IP) and the remove procedure (RP) to solve the MSCN problem. Preliminary computational experiments demonstrate the efficiency and performance of the proposed HHA.

As supply chains become bigger and dynamically structured involving multiple organizations with different interests, it is impossible for a single organization to control a whole supply chain. So, decentralization of decision rights is an inevitable facet of managing modern supply chains. However, controlling in a decentralized mode can fail without appropriate coordination mechanisms. When the agents of a supply chain are not willing to cooperate in terms of information sharing, the whole supply chain can exhibit expensive inefficiencies such as the bullwhip effect. In this paper, we design a trustworthy decentralized coordination mechanism for dynamic lot-sizing in distribution networks, as an effort to motivate information sharing. We design multiple auctions and each auction coordinates the plans of a supplier and its customers by trading the right of managing the supplier's inventory plan. The coordination mechanism makes a reasonable profit and the profit is divided in an agreeable way. Also, the profits are actual because of the capability of supporting a truth-telling environment. Therefore, the designed coordination mechanism is trustworthy in that it guarantees the right benefits to all the agents in return for information sharing.