Supply Chain Distribution Network Research Articles

Indonesian High-Speed Railway Optimization Planning for Better Decentralized Supply Chain Implementation to Support e-Logistic Last Miles Distribution

E-logistics must have better strategy because they must satisfy unpredictable demands which came from customer. Other consumer behaviours which affect e-logistics must work more efficiently are the requirement of last miles fast delivery and more competitive pricing. Decentralized supply chain model can handle all these issues and complex logistics activity although it only has one echelon model in the supply chain structure. Decentralized supply chain model doesn’t need a distribution centre but requires inventory sharing policy. Key to success inventory sharing policy is low lead time delivery. In Indonesia, only two transportation type which can handle product in low lead time, i.e., train cargo and aircraft cargo. Train cargo still needs high lead time but has low operation cost. Aircraft cargo can handle product in low lead time but need high operation cost. The trade-off in this condition is e-logistics need low lead time transportation tenant to satisfy demand until last miles delivery but has low operation cost not as expensive as aircraft cargo. Indonesia is developing high-speed train which connects Jakarta to Surabaya. In this research, we will review the level of effectiveness high-speed train in Indonesia to realized decentralized supply chain distribution network for handling e-logistics last miles shipping using dynamic system simulation. The output of this research is efficiency review of Indonesian high-speed railway cargo to support decentralized e-logistics supply chain distribution network, compared by aircraft cargo. After we perform simulation using dynamic system simulation, delivery of products between regions by using fast train is declared feasible to deliver products with fast delivery type if in one day there are six departure time (delivery batch). If less than six departures, the railway is declared unfeasible to deliver products with fast delivery type. However, the train can save about 37% batch delivery when compared to cargo aircraft.

A demand aggregation approach for inventory control in two echelon supply chain under uncertainty

In this paper it is discussed that the demand aggregation is an effective approach for reducing inventory levels and the number of facilities under the uncertain supply and demand conditions. Therefore in this paper, an inventory control model is developed incorporating demand aggregation approach for two staged supply chain distribution network under uncertain demand conditions. The two stage of distribution network mainly consists of distributors and retailers. This inventory control model is developed as non-linear programming model with in the different alternatives of distribution networks. The main decision variables of the system are reorder point and the ordering quantity. The prime objective function in this paper is the total cost of system which mainly consists of ordering cost, inventory carrying cost, facility cost, facility operating cost and the cost of shipment. The model is solved for total cost minimization which provides the optimum inventory policy (reorder point and ordering quantity) and the minimum cost. Through this problem best alternative of distribution network is also suggested along with optimum reorder point, ordering quantity and total cost of the system. Some other vital inventory performance parameters besides of ordering quantity and reorder point are also evaluated for the system. These performance parameters are safety stocks, expected shortages per cycle, fill rates, cycle service level, average inventory etc. These performance parameters are evaluated with total cost of the system under different uncertainty levels for a desired service level. This problem also yielded the best network options in given uncertain conditions of demand and supply. This model is formulated for single product and single period. This study mainly focused on the small part of supply chain i.e. distribution network for implementing demand aggregation approach. A case study of a sugar mill distribution network has been performed for validating the industrial applications of the proposed model.

Omni-Channel Product Distribution Network Design by Using the Improved Particle Swarm Optimization Algorithm

Distribution network under Omni-Channel integration contains many levels. There are one or more dealers at each level which forms a many-to-many distribution network. Consumers purchase a wide variety of products and their demands are uncertain, which constitutes a complex demand network and increases the complexity of the supply chain network. This paper focuses on the integrated optimization of supply chain distribution network and demand network and constructs the joint randomization planning model of location and routing. The goal is to minimize the total costs of the supply chain network under uncertain customer demands. Based on the traditional particle swarm optimization (PSO), this study introduces the collaborative idea to reduce the coding dimension, improves the boundary processing strategy, and adopts the mutation operator to expand the search space. A case study of distribution under Omni-Channel integration in a large enterprise was done. The validity of the model and the effectiveness of the proposed method were verified by numerical experiments.

On the Two-Stage Transportation Problem With Fixed Charge for Opening the Distribution Centers

In this paper, we are addressing the two-stage transportation problem with fixed charge for opening the distribution centers, which is an extension of the classical transportation problem. The problem models a distribution network in a two-stage supply chain which involves: manufacturers, distribution centers and customers, and its main characteristic is that a fixed charge for opening the distribution centers is associated, in addition to the variable transportation cost which is proportional to the amount of goods shipped. We describe a novel solution approach for the minimization of total distribution costs: a fast and efficient constructive heuristic algorithm that reduces the solution search space to a subspace with a reasonable size, without losing optimal or sub-optimal solutions by considering a perturbation mechanism that allows us to reconsider discarded feasible solutions that might lead to such solutions. Computational results are reported and discussed for the existing benchmark instances and on a set of instances that contains eight new randomly generated larger instances. The obtained results show that our solution approach is highly competitive as compared to the existing methods from the literature.

Universal Supply Chain Distribution Network: A Catalyst Towards Global Circular Economy and Sustainable Business Process

Universal Supply Chain Distribution Network: A Catalyst Towards Global Circular Economy and Sustainable Business Process

Design of a supply chain distribution network for communicable diseases: Hepatitis A in Jordan as a case study

Distribution network plays a vital role on the efficiency and the responsiveness of a supply chain. Any product or service goes through a network until it reaches the final customer. Health care systems incorporate distribution networks to better provide health services to patients. In this study, a distribution network for communicable diseases has been developed. The proposed network addresses Hepatitis A in Jordan as a case study, as it is considered one of the common communicable diseases in Jordan. A regression model was developed to predict future incidents of Hepatitis A in Jordan to build a distribution network based on the future required resources. An optimization clustering model was used to structure the appropriate distribution network. The proposed network was compared with the current network used for distribution of medications for Hepatitis A. The new network incurs less cost in delivering medications to the required hospitals as the traveling distance is less. As future work, it is recommended to incorporate more communicable diseases to develop more realistic distribution network.

A framework for designing a supply chain distribution network

Based on the analysis of the pertinent literature, we propose a framework to serve as a guide in designing a distribution network as a component of a supply chain (SC). It consists of three steps that are common to goods and services SCs: position of the decoupling point, structure of the network, and product delivery. For each step, we take into account the peculiarities of both goods and services separately in order to establish a list of available options and evaluate their suitability in relation to the relevant factors that characterise the products and the markets.

Proactive and reactive models for disaster resilient supply chain

Natural or man-made disasters lead to disruptions across entire supply chain, hugely affecting the entire distribution system. Owing to disaster, the supply chain usually takes longer time to recover and eventually leads to loss in reputation and revenue. Therefore, business organizations are constantly focusing on making its distribution network of a supply chain resilient to either man-made or natural disasters in order to satisfy customer demand in time. The supply chain distribution network broadly comprises of two major decisions i.e. facility location and vehicle routing. The paper addresses these distribution decisions jointly as location-routing problem. The paper proposes Location-Routing Model with Time Windows using proactive and reactive approaches. In proactive approach, the risk factors are considered as preventive measure for disaster caused disruptions. The model is extended for reactive approach by considering the disruptions such as facility breakdowns, route blockages, and delivery delays with cost penalties. The case illustration is discussed for proactive approach. In case of disaster caused disruptions, the reactive approach is illustrated using three disruption case scenarios. Using both proactive and reactive approach, designing the distribution system can make the overall supply chain a disaster resilient supply chain.

Designing the distribution network in a cassava supply chain in Thailand

According to Thailand’s infrastructure development and investment plan, an efficient transportation network will take form over the next three to five years. Dual-track railway will be built to cover more areas of the country and will be offered more routes between central, north-eastern, and eastern Thailand. Therefore, rail transportation or train transportation will become a good choice or an important conveyance of goods from various origins to various destinations in Thailand due to its competitiveness which is low cost of freight. This paper presents a concept of designing the new distribution network in Thailand using rail as a major mode of transportation. Cassava distribution chain is selected as a case study and prototype of this new design, since Thailand is an agricultural country and cassava is one the most exported agricultural product. Various factors influencing the choice of distribution network and transportation mode, such as customer satisfaction, characteristics of products, cost, etc., are investigated and are described. Linear programming models represent the current distribution model and the new distribution model are presented and then solved by Microsoft Excel with Open Solver Software. The result reveals that the new distribution network of cassava product in Thailand can lower the total distribution cost up to 51.63% compare to the current distribution network.

Performance of Transport Systems and Distribution Network of Green Supply Chain

Performance of Transport Systems and Distribution Network of Green Supply Chain

Designing a flexible multi-commodity distribution network in a multi-level supply chain

In response to the market competitive conditions today, organizations are increasingly striving to deliver products to customers in the correct volumes, at the right time, and in the right place. An important success factor in this competitive environment is employing an appropriate and efficient distribution network that is designed around the objectives of optimum numbers, locations, and capacities of production and distribution centers and an optimum strategy for the timely transfer of products from the plant or the warehouse to the customer.The present study aims to investigate the problem of designing a flexible distribution network in a multi-level supply chain by assuming direct shipment from the manufacturer to the customer. The problem is considered as a multi-commodity, static, and certain model in the form of mixed integer programming, with each of the production and distribution facilities having multi-capacity levels and their numbers considered as variables in the model. The restriction of distribution radius for production plant and distribution centers (warehouses) has been considered. Since the distribution network design problem is an NP-hard problem, a meta-heuristic approach based on the particle swarm optimization method was adopted to solve the problem. To evaluate the performance of the proposed approach, 32 test problems were solved. Comparison of the results indicates the efficiency of the proposed method.

Bullwhip Effect Analysis in Two-Level Supply Chain Distribution Network Using Different Demand Forecasting Technology

Following the basic work conducted by Lee et al. [(1997a), The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102; (1997b), Information distribution in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558] and using two first-order autoregressive AR(1) models, respectively, this paper provides three quantitative models of the bullwhip effect of the two-level supply chain distribution network consisting of a single manufacturer and two retailers. The paper assumes that two retailers adopt the order point method, uses three kinds of demand forecasting technology, i.e., moving average, exponential smoothing and minimum mean square error methods, respectively, provides three corresponding models for analyzing the impact of bullwhip effect of two-level supply chain distribution network. At the same time, this paper compares and analyzes the results of the three models through simulation.

The System Dynamics Model in Electronic Products Closed-Loop Supply Chain Distribution Network with Three-Way Recovery and the Old-for-New Policy

With the technological developments and rapid changes in demand pattern, diverse varieties of electronic products are entering into the market with reduced lifecycle which leads to the environmental problems. The awareness of electronic products take-back and recovery has been increasing in electronic products supply chains. In this paper, we build a system dynamics model for electronic products closed-loop supply chain distribution network with the old-for-new policy and three electronic products recovery ways, namely, electronic products remanufacturing, electronic component reuse and remanufacturing, and electronic raw material recovery. In the simulation study, we investigate the significance of various factors including the old-for-new policy, collection and remanufacturing, their interactions and the type of their impact on bullwhip, and profitability through sensitivity analysis. Our results instruct that the old-for-new policy and three electronic products recovery ways can reduce the bullwhip effect in the retailers and the distributors and increases the profitability in the closed-loop supply chain distribution network.

A Multiperiod Supply Chain Network Design Considering Carbon Emissions

This paper introduces a mixed integer linear programming formulation for modeling and solving a multiperiod one-stage supply chain distribution network design problem. The model is aimed to minimize two objectives, the total supply chain cost and the greenhouse gas emissions generated mainly by transportation and warehousing operations. The demand forecast is known for the planning horizon and shortage of demand is allowed at a penalty cost. This scenario must satisfy a minimum service level. Two carbon emission regulatory policies are investigated, the tax or carbon credit and the carbon emission cap. Computational experiments are performed to analyze the trade-offs between the total cost of the supply chain, the carbon emission quantity, and both carbon emission regulatory policies. Results demonstrate that for a certain range the carbon credit price incentivizes the reduction of carbon emissions to the environment. On the other hand, modifying the carbon emission cap inside a certain range could lead to significant reductions of carbon emission while not significantly compromising the total cost of the supply chain.

A location-inventory-pricing model in a supply chain distribution network with price-sensitive demands and inventory-capacity constraints

This paper presents a location-inventory-pricing model for designing the distribution network of a supply chain with price-sensitive demands and inventory-capacity constraints. The supply chain has market power and uses markup pricing. An efficient Lagrangian relaxation algorithm is proposed to solve the model. Our numerical study shows that by moderately increasing the number of possible values for pricing decisions, the model can be used to find near-optimal solutions of a similar location-inventory-pricing problem with continuous pricing decisions. The approach used here to incorporate pricing decisions can be applied to other supply-chain design and planning problems with price-sensitive demands.

Redesigning a Supply Chain Distribution Network: Formulation and Genetic Algorithm-Based Solution Procedure

Distribution affects company cost and customer satisfaction. Distribution network design is a strategic concern for nearly all companies, and must be periodically reviewed to ensure fitness to today's rapidly changing business environment. Unlike most of previous research, this paper investigates a highly complicated and realistic distribution network, and develops a multi-objective model to achieve an effective redesign solution. Reconfiguring cost, service differentiation, multiple products, and optional capacity levels are simultaneously considered. A determinant code-based encoding structure is designed to represent the complicated multi-objective optimization problem, and a genetic algorithm (GA)-based procedure is developed as a solution. The paper provides an application example using actual data. Finally, a comparison between the empirical results and those of the Prüfer-based GA demonstrate the efficiency of the proposed GA.

Agility and Proximity Considerations in Supply Chain Design

Strategic supply chain design decisions are critical to the long-term success of a business. Traditional facility location models for supply chain design focus on the trade-offs between the costs and benefits of proximity, i.e., the distance between facilities and customers. These strategic-focused models do not consider the supply chain’s agility, i.e., its ability to quickly respond to unexpected fluctuations in customer needs. In this paper, we study the problem of designing a supply chain distribution network under demand uncertainty and analyze how the optimal design characteristics of proximity and agility depend on various input parameters. We are able to draw managerial insights on how agility considerations may invalidate well-established and widely accepted qualitative results derived from traditional models. In particular, we show that it is optimal to increase the density of distribution centers (DCs) when the shortage penalty cost increases, and to decrease the density of DCs when a certain unit transportation cost parameter increases. Through these findings, our work conveys the message that traditional, proximity-based facility location models can be inadequate for designing modern responsive supply chains, and calls for the need to develop a new class of models for the task. This paper was accepted by Yossi Aviv, operations management.

Recycler Reaction for the Government Behavior in Closed-Loop Supply Chain Distribution Network: Based on the System Dynamics

With system dynamics, we establish three-closed-loop supply chain distribution network system model which consists of supplier, manufacturer, two retailers, and products (parts) recycler. We proposed that recycler make reflect for the government policy by adjusting the recycling ratio and recycling delay. We use vensim software to simulate this model and investigate how the products (parts) recyclers behavior influences the loop supply chain distribution system. The result shows that (1) when recyclers respond positively to government policies, recycling will increase the proportion of recyclers. When recyclers respond negatively to government policy making, recycling will reduce the proportion of recyclers. (2) When the recovery percentage of recyclers improves, manufacturers, Retailer 1, and Retailer 2 quantity fluctuations will reduce and the bullwhip effect will diminish. (3) When the proportion of recycled parts recyclers is lowered, manufacturers, Retailer 1, and Retailer 2 inventory fluctuation will increase and the bullwhip effect will be enhanced. (4) When recyclers recycling product delays increased, volatility manufacturers order quantity will rise, but there is little change in the amount of fluctuation of orders of the two retailers. (5) When recycling parts recyclers delay increases, fluctuations in the supplier order quantity will rise, but there is little change in the amount of fluctuation of orders of the two retailers.

Model for Building a Distribution Network Based on the Multivariate Analysis of the Industrial and Logistical Potential of Regions

The international integration of the Russian economy is connected to the need of the realization of the competitive advantages of the geopolitical position of Russia, the industrial potential of regions, the logistic infrastructure of transport corridors. This article discusses the design model of the supply chain (distribution network) based on the multivariate analysis and the methodology of the substantiation of its configuration based on the cost factors and the level of the logistics infrastructure development. For solving the problem of placing one or more logistics centers in the service area, a two-stage algorithm is used. At the first stage, the decisions on the reasonability of the choice of one or another version of the development are made with the use of the “Make or Buy†standard model. The criterion of decision making is the guaranteed overcoming of the threshold of “indifference†taking into account the statistical characteristics of costs for options of “buy†and “make†depending on the volume of consumption of goods or services. At the second stage, the Ardalan’s heuristic method is used for the evaluation of the choice of placing one or more logistics centers in the service area. The model parameters are based on the assessment of the development prospects of the region and its investment potential (existence and composition of employment, production, natural resources, financial and consumer opportunities, institutional, innovation, infrastructure capacity). Furthermore, such criteria as a regional financial appeal, professionally trained specialists, the competitive advantages of the promoted company and others are analyzed. An additional criterion is the development of the priority matrix, which considers such factors as difficulties of customs registration and certification, a level of regional transport infrastructure development, political risks and others. Fixing of regional consumers to this or that distribution center can be proved by the solution of open type transport problem. The result of the research is the development of optimal variants for placement of distribution centers based on the multivariate analysis. This model can be used in designing networks to promote products in the territories and regions whose accelerated socio-economic development is supposed.

Assessing effect of global inventory planning with enterprise-wide information for a large manufacturer

This paper studies how a global manufacturer with many subsidiaries can achieve enhanced business value for the organization by sharing information within its supply chain network. Specifically, the uncertainties in the demands from the downstream distribution center affect the inventory levels at the upstream distribution center under different inventory policies, considering the uncertain lead times and the given order fill rates. With a generic simulation model and real data, we evaluate the magnitude of savings in inventory under the new inventory policy where information can be shared among subsidiaries, compared to the status quo where subsidiaries run independently with no information sharing. The results show that average inventory level at the upstream DC under the new policy would be reduced by approximately 3%. Considering the given manufacturer's global supply chain distribution network holds about $4 billion in average inventory, the 3% improvement is a very significant savings.