Coordinated delivery in urban retail

In the Coordinated Delivery Problem (CDP), we study the passive and proactive coordination strategies that coordinate the delivery among urban retail stores. We formulate the CDP as mixed integer programs and develop a matheuristic, the effectiveness of which is evaluated via newly generated instances. Our numerical study shows that, when the stores prefer placing orders based on their own inventory policies, the proactive coordination strategy is able to achieve similar logistics and services performances to Vendor Managed Inventory (VMI), while respecting the store order decisions as under Retailer Managed Inventory (RMI), and thus offers an excellent combination of VMI and RMI

An Adaptive Large Neighborhood Search Heuristic for the Inventory Routing Problem with Time Windows

This research addresses an integrated distribution and inventory control problem which is faced by a large retail chain in the United States. In their current distribution network, a direct shipping policy is used to keep stores stocked with products. The shipping policy specifies that a dedicated trailer should be sent from the warehouse to a store when the trailer is full or after five business days, whichever comes first. Stores can only receive deliveries during a window of time (6 am to 6 pm). The retail chain is seeking more efficient alternatives to this policy, as measured by total transportation, inventory holding and lost sales costs. More specifically, the goal of this research is to determine the optimal timing and magnitudes of deliveries to stores across a planning horizon. While dedicated shipments to stores will be allowed under the optimal policy, options that combine deliveries for multiple stores into a single route should also be considered. This problem is modeled as an Inventory Routing Problem with time window constraints. Due to the complexity and size of this NP-hard combinatorial optimization problem, an adaptive large neighborhood search heuristic is developed to obtain solutions. Results are provided for a realistic set of test instances

Optimisation of a distribution system in the retail industry: An Australian retail industry

This paper develops a mathematical model based on inventory routing problem that aims to minimise transportation cost, inventory carrying cost and optimises delivery schedules in a retail Australian industry. A supply chain is considered which comprises of a single distribution centre, having homogenous fleet of vehicles, supplying a single product to multiple retailers having deterministic demand. The mathematical model takes into account varying level of road congestion.N/

AN INVENTORY ROUTING PROBLEM FOR DETERIORATING ITEMS WITH DYNAMIC DEMAND AND SPOILAGE RATE

Inventory routing problems (IRP) are among important tools to be used for implementing vendor manage inventory. Many researchers try to develop methods for solving inventory routing problem, however, only a few developed methods for inventory routing problems for spoilage items. In reality, many items are deteriorated and spoiled during transportation and storage period. In this paper, we developed a model and methodsto solve the inventory routing problem for deteriorating items with dynamic demand and spoilage rate, i.e., demand varies and items spoil during planning periods. Those cases are more realistic since many commodities such as fruits and vegetables have dynamic demand and spoilage rate. A Genetic Algorithm and Particle Swarm Optimization are developed to solve the problem with various demands in a specic planning period since the problem is Np-hard. A numerical example and sensitivity analysis are conducted to verify the model, and to get management insight it. The result is interesting and support general hypothesis that dynamic demands result in higher inventory cost than the static demands, and the increasing demand results in increasing inventory cost.mAlso, the results show that increasing demand and deteriorating rates signicantly affect the total cost, therefore, the developed model is important and signicantly useful to be used for solving IRP with dynamic demand and spoilage items

SIMULATION METHODS APPLICATION FOR LPG DELIVERIES PLANNING AND SCHEDULING TO THE NETWORK OF STATIONS UNDER DEMAND UNCERTAINTY

In our paper we considered the problem of demand uncertainty and its influence on planning and scheduling of LPG deliveries. The experience of specialized transportation company in charge of LPG deliveries for the domestic supplier network under VMI approach was analyzed. High variability of distribution parameters and frequent orders modifications were observed while small stations tanks capacities comparing to high daily LPG sales volumes were considered. The combined use of simulation and optimization methods was proposed for the case of LPG distribution to the petrol stations network. The demand uncertainty at customers' stations was considered. Simulation models were assumed to be efficient for dynamic and robust delivery plans of LPG distribution. The results of computational experiments were presented for different values of coefficient of variation

Optimizing Vendor-Buyer Inventory Model with Exponential Quality Degradation for Food Product Using Grey Wolf Optimizer

Inventory is an essential factor in the supply chain. Inventory problems are increasingly complex for perishable products such as food. This study proposes a Single Vendor-Single Buyer (SVSB) model for food products by considering exponential quality degradation. The objective function of this problem is to maximize the Joint Total Profit (JTP) of the SVSB system. The frequency of ordering raw materials (m), the frequency of delivery of the finished product (n), and the time of the inventory cycle (T) were the three (3) decision variables introduced in the study. This study proposes the Grey Wolf Optimizer (GWO) algorithm as an optimization tool for SVSB problems. A case study was conducted on a food company in Indonesia. Sensitivity analysis on costs, revenue, and JTP was also presented. The results showed that raw materials' quality degradation level affected JTP. The results also suggested that the GWO algorithm performs better than the Genetic Algorithm (GA) to optimize the SVSB inventory model

E-Fulfillment and Multi-Channel Distribution – A Review

This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in today’s e-commerce operations is the combination of ‘bricks-and-clicks’, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering.Distribution;E-fulfillment;Literature Review;Online Retailing

Optimization strategies for the integrated management of perishable supply chains: A literature review

Purpose: The main purpose of this article is to systematically review the papers published in the period 2005-2020 about the integration of production, inventory and distribution activities in perishable supply chains. Design/methodology/approach: The proposed research methodology is based on several steps. First, database and keywords are selected, with the aim to search and collect the main papers, dealing with the integration of production, inventory, distribution activities in perishable supply chains. Then, a bibliometric analysis is carried out, to detect: the main publishing sources, the chronological distribution, the most used keywords, the featured authors, about the selected papers. A five-dimension classification framework is proposed to carry out a content analysis, where the papers of the literature review are classified and discussed, according to: supply chain structure, objective, perishability type, solution approach, approach validation. Findings: Interest in the application of optimization models for integrated decision-making along perishable supply chains is strongly growing. Integrating multiple stages of the supply chain into a single framework is complex, especially when referring to perishable products. The vast majority of the problems addressed are then NP-Hard. Only a limited quantity of the selected papers aims to solve real-life case studies. There is a need for further research, which is capable of modeling and quantitatively improving existing supply chains. The potentials of Industry 4.0 are currently little explored. Originality/value: Based on the analysis of the papers published, this article outlines the current state of the art on the optimization strategies for the integrated management of perishable supply chains, which are very complex to be managed. Research trends and gaps are discussed, future challenges are presentedPeer Reviewe