Demand and distribution networks
The distribution network also depends of the demand. Depending how concentrated is the demand during the year, there will be different distribution networks. The case of toys its very different compared with the food industry. In the first case the whole distribution network
There are important aspects related with demand:
 Seasonal demand: Like on the toys
 Life cycle phase.
 Life limited products.
 Predictability level of demand: Thre are different methods of forecasting.
Warehouse at a Mercadona Supermarket
This is a picture I tool today on a Mercadona supermarket in Valencia. This is the warehouse they use beyond what they have on the aisles. Probably for mire than 2 days as we said during the lecture.
Fleet management
Sina and Janina made a presentation about fleet management. Fleet management comprises the target oriented, optimal planning, supervision and control of the fleet operations based on the availabe resources, considering internal and external influencing factors. A special focus is on the integration of organizational processes with modern information systems.
Fields of application:
 Obcject tracking (vehicle tracking): where are they, are they moving…
 Health and safety tracking: special important for police or ambulances.
 Fuel and speed management: Can be controlled from a center.
 Sales order transmission
 Route planning
 Driver management
 Vehicle diagnostics
Route planning:
Serves to arrange different transport orders to tours of a vehicle fleet. There are different standard problems like:
 Travelling salesman problem: Find the shortest way of a circular tour (starting point till end point) that is as cost effective as possible that visits a certain amount of customers exactly once.
 Vehicle routing problem: is an extension of the travelling salesman problem which various vehicles are available at a depot.
 Pickup and delivery problem: consignments are picked up at one place and transported to their destination.. Pick up locations and the destinations have to be in the same tour and a full truckload PDP is supposed. It’s similar to what some low cost airlines do like Ryan Air.
In route planning there are 2 approaches:
 Dynamic route planning.
 Static route planning.
Location tracking:
Controls supply chains and move products to the market faster. It is also necessary to monitor assets, prevent inventory loss and track vehicle fleets.
Companies must consider how to track inventory an a smaller area or across a wide area.
Related to tracking technologies there are different alternatives:
 RFID: Local area and indoor tracking.
 GPS: Signals received from satellites to track movements of objects moving great distances. A very interesting video about GPS can be found by clicking here.
Advantages:
 Improve efficiency and productivity
 Reduce operating costs
 Speed up logistics activities
 Transparency of all the transport events.
 Automatical data transfer from the order entry system.
 Optimal order distribution to the tours (cost, time and customer optimal).
This is a nice video about RFID:
Routing problems in transportation
What is a routing problem?
According to Ann Campbell from University of Iowa, the objective of routing problems in transportation is “to minimize the distribution costs during the planning period without causing stockouts at any of the customers”.
The most general case can be modelized by the Vehicle routing problem that broadly speaking consists on:
 Service a number of customers.
 Fleet of vehicles
 Looking for an optimal solution
It can be applied to several fields. In logistics, for instance, we could use it on invenvtory routing. This is an interesting case study of inventory routing:
“The Inventory Routing Problem (IRP) is concerned with the repeated distribution of a set of products from several facilities to a set of customers over a given planning horizon. The facilities produce these products at given rates and have ample storage capabilities for the products. The customers consume products at a given rate and have limited storage capabilities. A fleet of vehicles is available at each of the facilities as well as a set of drivers. The objective is to minimize the overall costs during the planning period.”
You can get the full case study including some data sheets by clicking here.
How can we solve a routing problem?
There are different ways to solve a routing problem, like:
 Dynamic programming
 Linear programming
 Genetic algorithms
 Bellman Ford Algorithm: It really computes the shortest path so probably it could not be used on routing because there would be some nodes without service. The video is really interesting.
Using graphs:
Using a graph is a very good way to represent this type of problems. Besides representing it graphically, there are other 2 interesting representations (Introduction to Algorithms – Thomas H. Cormen, Charles E. Leiserson and Ronald L. Rivest):
 As a collection of adjacency lists: It provides a compact way to represent sparse graphs (E is much less than V^2).
 Adjacency matrix: It’s use when the graph is dense (E is close to V^2).
There is open source software to represent graphs. I like quite a lot one called Grafos. Regardless the webpage is in Spanish, it’s quite good and simply to use. You can download it by clicking here.
General cases:
Routing vehicles:
Travel salesman problem:
Travel salesman with m routes:
Specific cases of the routing problem:
There are other interesting specific cases, like when you don’t know with certainty when planning customers loads demands. That one is called vehicle routing problem with stochastic demand. Here you can find some articles about this topic:
 A vehicle routing problem with stochastic demand – Dimitris J. Bertsimas – MIT: Here Prof. Bertsimas explains how to deal with this kind of problems. It’s interesting because by reading his webpage (research section) he says that his goal is “to propose a tractable theory for optimization under uncertainty”

Planning approximations to the average length of vehicle routing problems with time window constraints – Portland State University: Dr. Miguel Andres Figliozzi studies the average length of vehicle routing problems with time window, route duration and capacity constraints.
 Vehicle routing problem with time windows and a limited number of vehicles – Hoong Chuing Lau, Melvyn Sim and Kwong Meng Teo
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