LOGISTICS PLANNING

Dr M MATHIRAJANDepartment of Management Studies

Indian Institute of ScienceBangalore

LOGISTICS PLANNING

The Increased Importance of Logistics• A Reduction in Economic Regulation

• Recognition by Prominent Non-Logisticians

• Technological Advances

• The Growing Power of Retailers

• Globalization of Trade

Three objectives of logistics strategy:• Cost reduction (variable costs)• Capital reduction (investment, fixed costs)• Service Improvement (may be at odds with

the above two objectives).

Marketing orientation

(competitive advantage)

Time and place utility

Efficient movement to

customer

Proprietary asset

Natural resources (land, facilities, and equipments)

Human resources

Financial resources

Information resources

Management actions

Planning Implementation Control

Logistics Activities

•Customer Service

•Demand forecasting

•Distribution communications

•Inventory control

•Material handling

•Order Processing

•Parts and service support

•Plant and warehouse site selection

•Procurement

•Packaging

•Return goods handling

•Salvage and scrap disposal

•Traffic and transportation

•Warehousing and storage

Raw materials

In-process inventory

Finished goods

Inputs into logistics

Suppliers

Logistics management

Customers

Outputs of logistics

Components of logistics management :

To gain a better grasp of the fundamental trade-offs in logistics, I will divide logistics activities into three categories:

ProductionStorageTransportation

The term “Resource” applies to all of the factors of production, including materials (e.g., Iron, fabric, parts), equipment (e.g., machines or vehicles), energy (e.g., oil, coal, electricity) and labor.

PRODUCTION: Fundamental logistics questions are: (1) when should a resource be produced; and (2) where should a resource be produced.

The “when” question includes the topics of aggregate resource planning, and production scheduling.

The “where” question includes the topics of facility location and production allocation.

Some of the important production questions are:

(a) What outside source should be used to supply a part?

(b) Where should a new facility be built?

(c) When should a facility produce different items, taking into account:

• Seasonal demand patterns?

• Demand uncertainty?

• Cost of operating single, double, triple shifts?

• Labor costs?

(d) When should a firm use two or more sources for a part?

INVENTORY: Fundamental logistics questions are (1) when should a resource (material, machine or labor) be put in inventory and taken out of inventory; and (2) where should a resource be stored.

The “when” question includes the general topics of economic-order-quantity models, safety stock models and seasonal models, and specialized topics of fleet management, and personnel planning.

The “where” questions includes the topic of inventory echelons.

Some of the important inventory questions are:

(a) How much does it cost to store resources in inventory?

(b) How much “safety stock” should be carried in inventory to prevent against running out of a resource?

(c) How much inventory should be carried in order to smooth out seasonal variations in demand?

(d) Where should replacement parts be stored in multi-echelon inventory system?

TRANSPORTATION: Fundamental logistics are: (1) where should resources be moved to, and by what mode and route; (2) when should resources be moved.

The “where” question includes the topics of terminal location, vehicle routing, and shortest path methods and network flow allocation.

The “when” question includes the topic of distribution rules.

Some of the important questions are:

(a) When should shipment be sent through terminals, and when should shipment be sent direct?

(b) Which, and how many, terminals should shipments be sent through?

(c) What are the best vehicle routes?

(d) When should a vehicle be dispatched over a route?

Logistics - Science of managing (controlling) the movement and storage of goods (or people) from acquisition to consumption.

Goods: Raw Materials Final products, and everything in between.

Logistics for services & people similar to goods logistics.

Ex. Police, fire, ambulance, passenger airlines, taxi cabs, etc.

Movement = Transportation (between locations).

Storage = Inventory, Warehousing (at locations).

Difference between acquisition and consumption is a matter of space and time.

NOTE: Logistics does not deal with Technology of Production, such as the design of machines and vehicles and the design of finished products.

Focus: Best way to overcome space and time that separates acquisition and consumption.

1998 CLM DEFINITION OF LOGISTICS

….is that part of the supply chain process that

plans, implements, and controls the efficient,

effective flow and storage of goods, services,

and related information from the point-of-

origin to the point-of-consumption in order to

meet customers' requirements.

Council of Logistics Management, 1998; www.CLM1.org

Five Business Systems - Tightly Interconnected Within The Organization

Measurement Decisions

Management Systems

Reward Decisions

Strategic Decisions

Transportation Decisions

Sourcing Decisions

Inventory Decisions

Logistics Systems{

Price Decisions

Promotion Decisions

Marketing Systems

Product Decisions

Place (How, where, how

much)

}Production Scheduling Decisions

Production Capacity Decisions

Shop Floor Decisions

Manufacturing Systems}

Product Design

Decisions

Process Design

Decisions Engineering Systems}

Copyright 2000 - All Rights Reserved

Logistics – Mission [A Bill of “Rights”]

• Logistics embodies the effort to deliver:– the right product– in the right quantity– in the right condition– to the right place– at the right time– for the right customer– at the right cost

Activities and Logistics Decisions

Transportationrate and contract negotiationmode and service selectionrouting and scheduling

Inventoriesfinished goods policiessupply schedulingshort term forecasting

Warehousingprivate vs. publicspace determinationwarehouse configurationStock layout and dock designstock placementCross-docking

Facility Locationdetermining location, number

and size of facilitiesallocating demand to facilities

Customer Servicedetermining customer wantsdetermining customer response to service changes

Materials Handlingequipment selection equipment replacementorder picking procedures

Packaging design Order Processing

order procedure determinationProduction Scheduling

aggregate production quantitiessequencing and timing of production runs

Logistics Planning

• Decide what, when, how in three levels:

– Strategic – long range > 1 year

– Tactical - < 1 year horizon

– Operational – frequently on hourly or daily basis

Examples of Decisions

Type Strategic Tactical Operational

Location

Transportation

Order Processing (CS)

#Facilities, size, location

Mode

Selecting order entry system

Inventory positioning

Seasonal Service Mix

Priority rules for customers

Routing

Replenishment Qty and timing

Expediting orders

The Logistics (Strategic) Planning TriangleThe Logistics (Strategic) Planning Triangle

Which mode?Which carrier?Which route?Shipment size and frequency?

Where?, How many? What size?Allocation?

Strategy/Control system?How much?

Where?

Transport Fundamentals

• Transport involves – equipment (trucks, planes, trains, boats, pipeline), – people (drivers, loaders & un-loaders), and – decisions (routing, timing, quantities, equipment size,

transport mode). When deciding the transport mode for a given product there are several things to consider:

• Mode price• Transit time and variability (reliability)• Potential for loss or damage.

NOTE: In developing countries we often find it necessary to locate production close to both markets and resources, while in countries with developed distribution systems people can live in places far from production and resources.

Most important component of logistics cost.Usually 1/3 - 2/3 of total cost.

Routes of Goods

Goods at

shippers

Freight forwarde

r warehou

se

Air termin

al

planeair

Freight forwarde

r warehou

se

Goods at consigne

es

Container

terminal

vesselsea

May change transpor-tation modes

truck

land railway

land

barge

mid-stream

pier

bulk goods

sea

let us guess

Air

•Rapidly growing segment of transportation industry•Lightweight, small items [Products: Perishable and time sensitive goods: Flowers, produce, electronics, mail, emergency shipments, documents, etc.]•Quick, reliable, expensive•Often combined with trucking operations

Rail

•Low cost, high-volume [Products: Heavy industry, minerals, chemicals, agricultural products, autos, etc.] •Improving flexibility

•intermodal serviceTruck

•Most used mode •Flexible, small loads [Products: Medium and light manufacturing, food, clothing, all retail goods]

•Trucks can go door-to-door as opposed to planes and trains.

Single-mode Service Choices and Issues

Water •One of oldest means of transport•Low-cost, high-volume, slow •Bulky, heavy and/or large items (Products: Nonperishable bulk cargo - Liquids, minerals, grain, petroleum, lumber, etc )]•Standardized shipping containers improve service•Combined with trucking & rail for complete systems•International trade

Pipeline •Primarily for oil & refined oil products•Slurry lines carry coal or kaolin•High capital investment•Low operating costs•Can cross difficult terrain •Highly reliable; Low product losses

Single-mode Service Choices and Issues (Contd.)

Transport Cost Characteristics

– Fixed costs:• Terminal facilities• Transport equipment• Carrier administration• Roadway acquisition and maintenance

[Infrastructure (road, rail, pipeline, navigation, etc.)]

– Variable costs:• Fuel• Labor• Equipment maintenance• Handling, pickup & delivery, taxes

NOTE: Cost structure varies by mode

Transport Cost Characteristics

• Rail– High fixed costs, low variable costs– High volumes result in lower per unit (variable) costs

• Highway– Lower fixed costs (don’t need to own or maintain roads)– Higher unit costs than rail due to lower capacity per truck– Terminal expenses and line-haul expenses

• Water– High terminal (port) costs and high equipment costs (both fixed)– Very low unit costs

• Air– Substantial fixed costs– Variable costs depend highly on distance traveled

• Pipeline– Highest proportion of fixed cost of any mode due to pipeline

ownership and maintenance and extremely low variable costs

Vehicle Routing:

- Separate single origin and destination:

Once we have selected a transport mode and have goods that need to go from point A to point B, we must decide how to route a vehicle (or vehicles) from point A to point B.

Given a map of all of our route choices between A and B we can create a network representing these choices The problem then reduces to the problem of finding the shortest path in the network from point A to B.

This is a well solved problem that can use Dijkstra’s Algorithm for quick solution of small to medium (several thousand nodes) sized problems.

Suppose we have multiple sources and multiple

destinations, that each destination requires some integer

number of truckloads, and that none of the sources have

capacity restrictions [No Capacity Restriction].

In this case we can simply apply the transportation method

of linear programming to determine the assignment of

sources to destinations. Sources Destinations

Vehicle Routing:

- Multiple Origin and Destination Points

- Coincident Origin and Destination: The TSP

• If a vehicle must deliver to more than two customers, we must decide the order in which we will visit those customers so as to minimize the total cost of making the delivery.

• We first suppose that any time that we make a delivery to customers we are able to make use of only a single vehicle, i.e., that vehicle capacity of our only truck is never an issue.

• In this case, we need to dispatch a single vehicle from our depot to n - 1 customers, with the vehicle returning to the depot following its final delivery.

• This is the well-known Traveling Salesman Problem (TSP). The TSP has been well studied and solved for problem instances involving thousands of nodes. We can formulate the TSP as follows:

Vehicle Routing:

TSP Formulation

– Minimize

– Subject to:

c xij ijj Ji I

x i I

x j J

x U U N

x i I j J

ijj J

iji I

iji j E U

ij

1

1

1

,

,

,

{0,1}, ( , ) ( )

,

In the TSP formulation if we remove the third constraint set we have the simple assignment problem, which can be easily solved. The addition of the third constraint set, commonly called sub-tour elimination constraints, makes this a very difficult problem to solve.

Questions about the TSP

• Given a problem with n nodes, how many distinct feasible tours exist?

• How many arcs will the network have?• How many xij variables will we have?• How could we quantify the number of subtour

elimination constraints?• The complexity of the TSP has led to several heuristic

or approximate methods for finding good feasible solutions. The simplest solution we might think of is that of the nearest neighbor.

Vehicle Routing: TSP, inventory routing, and vehicle routing

• Traveling Salesman Problem (TSP): salesman visits n cities at minimum cost

• vehicle routing problem (VRP): m vehicles with capacity to deliver to n customers who have volume requirement, time windows, etc.

• Inventory Routing: m vehicle to delivery to n customer with time windows, vehicle and storage capacity constraints, and un-specificed amount to be delivered.

• Heuristics1. Load points closest together on the same truck2. Build routes starting with points farther from depot first3. Fill the largest vehicle to capacity first4. Routes should not cross5. Form teardrop pattern routes.

6. Plan pickups during deliveries, not after all deliveries have been made.

Illustration of VRP

(Outlier)

Depot

50

76

39

112

88

2912344

5890

77

89

57

115124

59 176

65

98 125Truck Capacity = 250What is the minimum # of trucks we would need? Maximum?

Vehicle Routing

• Find best vehicle route(s) to serve a set of orders from customers.

• Best route may be– minimum cost,– minimum distance, or – minimum travel time.

• Orders may be– Delivery from depot to customer.– Pickup at customer and return to depot.– Pickup at one place and deliver to another place.

Complications

• Multiple vehicle types.

• Multiple vehicle capacities.– Weight, Cubic feet, Floor space, Value.

• Many Costs:– Fixed charge.– Variable costs per loaded mile & per empty mile.– Waiting time; Layover time.– Cost per stop (handling).– Loading and unloading cost.

• Priorities for customers or orders.

–Pure Pickup or Delivery Problems.–Mixed Pickups and Deliveries.–Pickup-Delivery Problems.–Backhauls

More Complications

• Time windows for pickup and delivery.– Hard vs. soft

• Compatibility– Vehicles and customers.– Vehicles and orders.– Order types.– Drivers and vehicles.

• Driver rules (DOT)– Max drive duration = 10 hrs. before 8 hr. break.– Max work duration = 15 hrs. before 8 hr break.– Max trip duration = 144 hrs.

Simple Models

• Homogeneous vehicles.

• One capacity (weight or volume).

• Minimize distance.

• No time windows or one time window per customer.

• No compatibility constraints.

• No DOT rules.

VRP Solutions

• Heuristics– Construction: build a feasible route.– Improvement: improve a feasible route.

• Not necessarily optimal, but fast.• Performance depends on problem.• Worst case performance may be very poor.

• Exact algorithms– Integer programming.– Branch and bound.

• Optimal, but usually slow and applicable for small size problem

• Difficult to include complications.

The VRP is applicable in many practical situations directly related to

the physical delivery of goods such as

distribution of petroleum products,

distribution of industrial gases,

newspaper deliveries,

delivery of goods to retail store,

garbage collection and disposal,

package pick-up and delivery,

milk pick-up and delivery, etc.

the non-movement of goods such as

picking up of students by school buses,

routing of salesmen,

reading of electric meters,

preventive maintenance inspection tours,

employee pick-up and drop-off , etc.

APPLICATIONS OF VRP

A DSS

Employee Bus Routing

Commodity Distribution

In COVERS

Efficient Heuristic Procedures

NNH

MNNH

MSCWH

Simulation Features

Manipulate the System Generated Routes

Completely User Generated Routes

COVERS Handles

Multi-Depot VRP

Heterogeneous VRP

COVERS- COMPUTERIZED VEHICLE ROUTING SYSTEM

EMPLOYEE PICKUP VEHICLE ROUTING PROBLEM (EPVRP) –

BANGALORE, KARNATAKA, INDIA

Indian Telephone Industries [ITI] Limited

Bharat Electronics Limited [BEL]

Hindustan Machine Tools [HMT]

Hindustan Aeronautics Limited [HAL]

Indian Space Research Organization [ISRO]

National Aeronautical Laboratory [NAL]

Central Machine Tools of India [CMTI]

………

AS A PROBLEM IN OR, A SIMPLIFIED EPVRP CAN BE DESCRIBED AS FOLLOWS:

GIVEN

A set (fixed number) of pick-up or delivery points, The demand at every pick-up or delivery points (deterministic), A set (fixed number) of vehicles (homogeneous) and All relevant distance information across pick-up points.

IT IS REQUIRED TO FIND AN EFFECTIVE/EFFICIENT SOLUTION FOR

Assigning pick-up points to vehicles and Sequencing pick-up points on the route of each vehicle

SO AS TO ACHIEVE THE OBJECTIVE OF

Minimizing the total distance traveled by the vehicles and/or the number of vehicles used.

UNDER THE CONSTRAINTS THAT Every route originates and terminates at the depot The capacity of vehicle is restricted The maximum distance (time) allowed for a vehicle on any route is within a pre-

specified limit Each pick-up point is visited once only Etc.,

AN ILP FORMULATION - EPVRPSource : WATERS (1998)

ASSUMPTIONS

Vehicle capacity is known and constant (homogenous)

The number of vehicles available is known (at least the minimum number of vehicles required is known)

The demand at every pick-up point is known (deterministic)

Maximum distance to be traveled by each vehicle is known and constant for all vehicles

Demand at every pick-up point is less than or equal to vehicle capacity

Every pick-up point is served by only one vehicle

Further, keeping in line with Water’s formulation, the model formulation is oriented towards routing during drop-back rather than pick-up. It is assumed that the reverse logic holds good for pick-up.

Expanding the Scope of Linear Programming Solutions for Vehicle Scheduling Problems. OMEGA, 16(6), 577-583

COMPUTATIONAL COMPLEXITY - OPTIMAL SOLUTION

# PUP

Tot Quantities

(Units)

# Variables Including (0, 1)

Variables

# (0, 1) Variables

# Constraints

Optimal Distance

(Km.)

# Routes # Iterations (LINDO)

CPU Time (AT 486)

4 61 48 16 60 13.2 1 45 2

5 71 75 25 85 26.4 2 330 3

6 79 108 36 114 28.6 2 353 6

7 106 147 49 147 31.0 2 2780 23

8 117 192 64 187 31.0 2 70724 80

9 132 243 81 225 37.4 2 43021 667 (11 Mts)

10 137 300 100 270 47.8 3 4963340 100800 (28 Hrs.)

Sutcliffe and Board (1990) estimated that a simple extrapolation of Waters’ (1988) ILP approach using

the SCICONIC software might take nearly 1,20,000 years of CPU time on a VAX 8600 machine to solve

a VRP with 38 pick-up points!

Optimal Solution of VRP: Transporting Mentally Handicapped Adults to an Adult Training Center. JORS, 41(1), 61-67.

Nearest Insertion Heuristic (NIH)

Cheapest Insertion Heuristic (CIH)

Parallel Version of Clarke & Wright Heuristic (PCWH)

Sequential Version of Clarke & Wright Heuristic (SCWH)

Convex Hull Heuristic (CHH)

Nearest Neighbour Heuristic (NHH)

Modified NNH (MNNH)

Modified SCWH 1 (MSCWH-1)

Modified SCWH 2 (MSCWH-2)

HEURISTIC ALGORITHMS

CASE STUDY : DETAILS OF ROUTES, DISTANCES & SEAT UTILIZATION

Shift Timings # Commuters

# Pickup Points

# Routes

Total Distance per Trip

(Km.)

Seat Utilization (%)

A 06.15 – 02.15 PM 3659 303 64 1977.0 89.0

FG 07.30 – 04.15 PM 3999 313 66 2163.0 94.3

AG 08.45 – 05.30 PM 3042 286 53 1808.3 90.0

B 02.15 – 10.15 PM 975 242 30 1056.7 54.0

C 10.15 – 06.15 AM 40 ---- ---- ---- ----

Total

11715 410 213+ (426)

7005.0 (14010)

----

Ignored in our study

Each Bus Route (Trip) Repeated; Two Trips a day, Once for Pick-up and once for Drop-off.

Distinct Pick-up Points

COMPARATIVE PERFORMANCE (CASE STUDY) – TOTAL DISTANCE

Procedures Shift – 1

A

Shift – 2

FG

Shift – 3

AG

Shift – 4

B

Total Distance (Km.)

Savings (in %)

CPU Time PC/AT – 486 @ 33 MHz (Minutes)

Existing Practice (Manual)

1977.0 2163.0 1808.3 1056.7 7005.0 ----- ----

NIH 1875.8 2047.7 1734.1 890.3 6547.9 6.5 12

CIH 2155.2 2322.3 1914.2 1020.7 7412.4 - 5.8 52

PCWH 1803.5 2026.1 1761.1 1080.9 6671.6 4.76 19

SCWH 2139.2 2306.6 1889.2 1014.5 7349.5 - 4.9 18

CHH 1903.8 2047.7 1749.2 964.7 6665.4 4.85 55

NNH 1822.9 2063.2 1708.0 900.0 6494.1 7.29 1

MNNH 1817.7 2040.8 1740.7 858.9 6458.1 7.81 1

MSCWH-1 1796.2 2066.4 1687.5 910.2 6460.3 7.78 2

MSCWH-2 1799.4 2047.0 1688.5 908.5 6443.4 8.02 2

(Figures in Table represent travel distance in Km. For Pick-up only)

COMPARATIVE PERFORMANCE (CASE STUDY) – TOTAL NUMBER ROUTES

Procedures Shift – 1

A

Shift – 2

FG

Shift – 3

AG

Shift – 4

B

Total Routes Reduction in Trips (%)

Existing Practice (Manual)

64 66 53 30 213 -----

NIH 60 63 51 23 197 7.51

CIH 65 69 52 27 213 0

PCWH 63 68 56 36 223 - 4.7

SCWH 65 70 55 28 218 - 2.3

CHH 60 62 51 25 198 7.04

NNH 57 64 50 24 195 8.45

MNNH 57 63 51 23 194 8.92

MSCWH-1 58 63 49 24 195 8.45

MSCWH-2 58 63 49 24 194 8.92

Figures in Table represent number of trips for Pick-up only

Nearest Neighbour Heuristic (NHH)

Modified NNH (MNNH)

Modified SCWH-2 (MSCWH-2)

HEURISTIC ALGORITHMS - DSS IMPLEMENTATION

A Schematic Diagram of COVERS

DATA MANAGEMENT MODULE

General file

Depot Data File

Vehicle Data File

Pickup point Demand Data File

Inter-Stop Distance Data File

MODEL MANAGEMENT MODULE

Heuristic Procedures

Simulation Model

REPORT MANAGEMENT MODULE Details of Route Sequence Summary of Routes Overall Summary of Routes Depot wise Route Allocation Vehicle Type wise Route Allocation

CONTROL MODULE

COMPUTER SYSTEM

USER