Modeling and Controlling of an Integrated Distribution Supply Chain: Simulation Based Shipment Consolidation Heuristics

Increasing competition due to market globalization, product diversity and technological breakthroughs stimulates independent firms to collaborate in a supply chain that allows them to gain mutual benefits. This requires collective knowledge of the coordination and integration mode, including the ability to synchronize interdependent processes, to integrate information systems and to cope with distributed learning. The Integrated Supply Chain Problem (ISCP) is concerned with coordinating the supply chain tires from supplier, production, inventory and distribution delivery operations to meet customer demand with an objective to minimize the cost and maximize the supply chain service levels. In order to achieve high performance, supply chain functions must operate in an integrated and coordinated manner. Several challenging problems associated with integrated supply chain design are: (1) how to model and coordinate the supply chain business processes; (2) how to analyze the performance of an integrated supply chain network; and (3) how to evaluate the dynamic of the supply chain to obtain a comprehensive understanding of decision-making issues related to supply network configurations. These problems are most representative in the supply chain theory’s research and applications. A particular real life supply chain considered in this study involves multi echelon and multi level distribution supply chains, each echelon with its own inventory capacities and multi product types and classes. Optimally solving such an integrated problem is in general not easy due to its combinatorial nature, especially in a real life situation where a multitude of aspects and functions should be taken into consideration. In this dissertation, the simulation based heuristics solution method was implemented to effectively solve this integrated problem. A complex real life simulation model for managing the flow of material, transportation, and information considering multi products multi echelon inventory levels and capacities in upstream and downstream supply chain locations supported by an efficient Distribution Requirements Planning model (DRP) was modeled and developed named (LDNST) involving several sequential optimization phases. In calibration phase (0), the allocation of facilities to customers in the supply chain utilizing Add / Drop heuristics were implemented, that results in minimizing total distance traveled and maximizing the covering percentage. Several essential distribution strategies such as order fulfillment policy and order picking principle were defined in this phase. The results obtained in this phase were considered in further optimization solutions. The transportation function was modelled on pair to pair shipments in which no vehicle routing decision was considered, such an assumption generates two types of transportation trips, the first being Full Truck Load trips (FTL) and the second type being Less Truck Load trips (LTL). Three integrated shipment consolidation heuristics were developed and integrated into the developed simulation model to handle the potential inefficiency of low utilization and high transportation cost incurred by the LTL. The first consolidation heuristic considers a pure pull replenishment algorithm, the second is based on product clustering replenishments with a vendor managed inventory concept, and the last heuristic integrates the vendor managed inventory with advanced demand information to generate a new hybrid replenishment strategy. The main advantage of the latter strategy, over other approaches, is its ability to simultaneously optimize a lot of integrated and interrelated decisions for example, on the inventory and transportation operations without considering additional safety stock to improve the supply chain service levels. Eight product inventory allocation and distribution strategies considering different safety stock levels were designed and established to be considered as main benchmark experiments examined against the above developed replenishment strategies; appropriate selected supply chain performance measures were collected from the simulation results to distinguish any trading off between the proposed distribution strategies. Three supply chain network configurations were proposed: the first was a multi-echelon distribution system with an installation stock reorder policy; the second proposed configuration was Transshipment Point (TP) with a modified (s,S) inventory; and the last considered configuration was a Sub-TP, a special case from the second configuration. The results show that, depending on the structure of multi-echelon distribution systems and the service levels targets, both the echelon location with installation stock policy and advanced demand information replenishment strategy may be advantageous, and the impressive results and service level improvements bear this out. Considering the complexity of modeling the real life supply chain, the results obtained in this thesis reveal that there are significant differences in performance measures, such as activity based costs and network service levels. A supply chain network example is employed to substantiate the effectiveness of the proposed methodologies and algorithms

SUPPLY CHAIN INTEGRATION IN THE FOOD AND CONSUMER GOODS INDUSTRIES

The interorganizational structures necessary to implement and achieve the logistical performance improvements identified in the Efficient Consumer Response (ECR) initiative and related supply chain management concepts are difficult to develop. Firms continue to struggle to implement integrated programs and techniques, particularly with respect to changing operating structures, relationships, and mindsets to facilitate true supply chain integration. This research explores the logistical strategies and structures used by selected food and consumer goods firms to integrate their supply chains. It illustrates effective integration strategies and identifies critical success factors and barriers to successful ECR implementation. A framework is used to guide managers in developing the competencies essential to integrating the supply chain and to establishing the relationships necessary to operate in an ECR environment. The framework, entitled Supply Chain 2000, depicts supply chain value creation as achieving synchronization and coordination across four critical supply chain flows: product/service; market accommodation; information; and cash.Industrial Organization,

The problem of production-distribution under uncertainty based on Vendor Managed Inventory

In this paper, a problem of managed inventory by the vendor in the production-distribution supply chain is presented based on the scenario. The main purpose of presenting the model of maximizing producer profit in a three-level supply chain network consisting of various strategic and tactical decisions under uncertainty. Due to the nonlinearity and NP-Hardness of the problem, meta-heuristic genetic algorithms, Whale optimization algorithm and league champions algorithm have been used. The results of problem solving show the high efficiency of meta-heuristic algorithms compared to accurate methods in solving the above model. So that the maximum percentage of relative differences between the methods mentioned with GAMS is less than 1%.Also, by solving the sample problems in larger sizes, it was observed that the league champions algorithm has the highest efficiency in terms of achieving the optimal value of the target function in a shorter time than the other algorithms used, with a useful weight of 0.998

Vendor Managed inventory, from concept to processes, for an unified view

International audienceIn a supplier-customer relationship, Vendor Managed Inventory (VMI) is currently used to monitor the customer's inventory replenishment. However the integration of VMI implies consequences on the collaboration process that links the different planning processes of each partner. This paper proposes a unified view of the VMI: beyond the short term pull system inventory replenishment, partners have to share their vision of the demand, their requirements and their constraints to fix middle/long term common objectives for each article concerned by VMI. There are many ways to specify these links between VMI and partner's planning processes

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs)

Optimal Supply Network with Vendor Managed Inventory in a Healthcare System with RFID Investment Consideration

Supply Chain Management in the healthcare sector faces several significant challenges, including complexity in healthcare systems, high supply chain costs, balancing quality and costs, delay in delivery, product availability from vendors, inventory waste, and unpredictability and uncertainty. Among those challenges, having an effective inventory management system with an optimal supply network is important to improve the match between supply and demand, which would improve the performance of for healthcare firms. Vendor Managed Inventory (VMI) system is a replenishment solution in which the vendor monitors and decides the time and the quantity of the inventory replenishment of their customers subject to their demand information exchange. A VMI contract in the location-inventory assignment problem is a decision tool for management in the healthcare industry, in which it enables the management to have a cost and service effective decision tool to critically re-evaluate and examine all areas of operations in a SC network looking for avenues of optimization. This dissertation is based on a real-world problem arising from one of the world\u27s leading medical implant supply company applied to a chain of hospitals in the province of Ontario. The chain of hospitals under study consists of 147 hospitals located in Ontario, Canada. The vendor is a supplier of three types of medical implants (a heart valve, an artificial knee, and a hip). In Chapter 2 of this dissertation, we present an optimal supply healthcare network with VMI and with RFID consideration, in which we shed light on the role of the VMI contract in the location-inventory assignment problem and integrate it with both the replenishment policy assignment and the Radio Frequency Identification (RFID) investment allocation assignment in healthcare SC networks using both VMI and direct delivery policies. A numerical solution approach is developed in the case of the deterministic demand environment, and we end up with computational results and sensitivity analysis for a real-world problem to highlight the usefulness and validate the proposed model. We extend our research of integrating the VMI contract in the location-inventory assignment problem with the replenishment policy assignment under a deterministic demand environment to include the stochastic demand environment. The impact of the uncertainty of the demand as a random variable following two types of distributions, normal and uniform distributions, is studied in Chapter 3. Motivated by the lack of investigations and comparative studies dealing with the preference of dealing with VMI contracts to other traditional Retailer Managed Inventory (RMI) systems, we provide in Chapter 4 of this dissertation a comparative study in which we compare the total cost of the VMI system with another two situations of traditional RMI systems: first, a traditional RMI system with a continuous replenishment policy for all hospitals and with assigned storage facilities and second, a traditional RMI system with a direct delivery policy for all hospitals without assigning a storage facility. Computational results, managerial insights, sensitivity analysis, and solution methodologies are provided in this dissertation. Keywords: Vendor Managed Inventory, healthcare system, location-inventory, RFID technology, supply-chain network, stochastic demand, location-inventory assignment problem, and retailer managed Inventory

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications