scholarly journals Integrated Inventory Routing Problem with Quality Time Windows and Loading Cost for Deteriorating Items under Discrete Time

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Tao Jia ◽  
Xiaofan Li ◽  
Nengmin Wang ◽  
Ran Li
Keyword(s):  
Discrete Time ◽  
Production Scheduling ◽  
Time Window ◽  
Mixed Integer ◽  
Time Interval ◽  
Second Phase ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Integrated Inventory

We investigate an integrated inventory routing problem (IRP) in which one supplier with limited production capacity distributes a single item to a set of retailers using homogeneous vehicles. In the objective function we consider a loading cost which is often neglected in previous research. Considering the deterioration in the products, we set a soft time window during the transportation stage and a hard time window during the sales stage, and to prevent jams and waiting cost, the time interval of two successive vehicles returning to the supplier’s facilities is required not to be overly short. Combining all of these factors, a two-echelon supply chain mixed integer programming model under discrete time is proposed, and a two-phase algorithm is developed. The first phase uses tabu search to obtain the retailers’ ordering matrix. The second phase is to generate production scheduling and distribution routing, adopting a saving algorithm and a neighbourhood search, respectively. Computational experiments are conducted to illustrate the effectiveness of the proposed model and algorithm.

Multi-Product Inventory-Routing Problem in the Supermarket Distribution Industry

2015 ◽  
Vol 11 (6) ◽  
pp. 747-766 ◽  
Author(s):  
Demetrio Laganà ◽  
Francesco Longo ◽  
Francesco Santoro
Keyword(s):  
Time Horizon ◽  
Soft Drink ◽  
Time Windows ◽  
Second Phase ◽  
Inventory Routing ◽  
Inventory Policies ◽  
Routing Problem ◽  
Delivery Strategy ◽  
Inventory Routing Problem ◽  
Varying Demand

Abstract The Inventory Routing Problem (IRP) is an integrated logistic problem arising in several industries (e.g. petrochemical, grocery, soft drink and automotive). A vendor decides the optimal delivery strategy for a set of customers, taking into account their inventory policies and avoiding product stock-out in a finite and discrete time horizon. Delivery strategy includes the time and size of deliveries in order to minimize the total delivery cost. Most commonly studied are IRP real cases where a single homogeneous product with deterministic but time-varying demand is delivered over a finite time horizon. This paper is focused on an efficient methodology for industrial problems where a vendor resupplies a set of customers of heterogeneous products (as in the supermarket distribution industry). In this context, the paper reports on an effort facing the inventory routing problem for multi-category products per customer in conjunction with different inventory policies per category. The paper is motivated by real applications arising in the food engineering field. For instance, industries dealing with food’s distribution to stores located in a given geographic area. The planning strategy is formulated as a linear model. The core of the decision problem consists in determining both the delivery route and the corresponding day of activation along the time horizon. A decomposition of the problem into two phases has been proposed. A suitable penalty cost modeled by simulating the possibility of having an early or delayed product delivery on the delivery day returned from the inventory model (e.g. Economic Order Quantity) is the key feature of the first phase. In the second phase, deliveries are scheduled on a daily basis by taking into account the time windows associated to each customer. This is accomplished by using a constructive heuristic algorithm for the vehicle routing problem with time windows. Computational results on some realistic instances are presented and discussed.

scholarly journals Discrete time and continuous time formulations for a short sea inventory routing problem

2016 ◽  
Vol 18 (1) ◽  
pp. 269-297 ◽  
Author(s):  
Agostinho Agra ◽  
Marielle Christiansen ◽  
Alexandrino Delgado
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem

scholarly journals Multi-product multi-vehicle inventory routing problem with vehicle compatibility and site dependency: A case study in the restaurant chain industry

2021 ◽  
Vol 9 (2) ◽  
pp. 351-362 ◽  
Author(s):  
Shunichi Ohmori ◽  
Kazuho Yoshimoto
Keyword(s):  
Mixed Integer ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Vehicle Type ◽  
Experiment Verification ◽  
A Site ◽  
Site Dependency ◽  
Restaurant Chain

We study an inventory routing problem (IRP) for the restaurant chain. We proposed a model a multi-product multi-vehicle IRP (MMIRP) with multi-compatibility and site-dependency (MMIRP-MCSD). The problem was formulated as a mixed integer programming (MIP). This model is difficult to solve because it is a problem that integrates MMIRP, a multi-compartment vehicle routing problem (MCVRP), and a site dependent VRP (SDVRP), each of which is difficult even by itself. Therefore, in this study, we proposed three-stage Math Heuristics based on the cluster-first and route-second method. In the numerical experiment, verification was performed using actual data, and knowledge on the decision making of the optimum vehicle type was obtained.

scholarly journals STRATEGY OF SOLUTION FOR THE INVENTORY ROUTING PROBLEM BASED ON SEPARABLE CROSS DECOMPOSITION

2005 ◽  
Vol 3 (02) ◽  
Author(s):  
M. Elizondo-Cortés ◽  
R. Aceves-García
Keyword(s):  
Second Phase ◽  
Ranking Algorithm ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Three Phase ◽  
Long Time ◽  
Np Hard Problem ◽  
Cross Decomposition ◽  
Key Questions

The Inventory-Routing Problem (IRP) involves a central warehouse, a fleet of trucks wlth finlte capacity, a set of customers, and a known storage capacity. The objective is to determine when to serve each customer, as well as what route each truck should take, with the lowest expense. IRP is a NP-hard problem, this means that searching for solutions can take a very long time. A three-phase strategy is used to solve the problem. This strategy is constructedn by answering the key questions: Which customers should be attended in a planned period? What volume of n products should be delivered to each customer? And, which route should be followed by each truck? The second phase uses Cross Separable Decomposition to solve an Allocation Problem, in order to answer questions two and three, solving a location problem. The result is a very efficient ranking algorithm O(n3) for large cases of the lRP.

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