Towards automated procurement via agent-

aware negotiation support

Andrea Giovannucci, Juan A. Rodríguez-Aguilar

Antonio Reyes, Jesus Cerquides, Xavier Noria

Ljubljana March 1st 2005

Artificial Intelligence Research Institute

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Motivation

Requirements

Model

Implementation

Demo

Agenda

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Motivation. Parts purchasingFRONT SUSPENSION, FRONT WHEEL BEARING ACQUISITION

PART NUMBER

DESCRIPTION UNITS

1 FRONT HUB 2

7 LOWER CONTROL ARM BUSHINGS

3

8 STRUT 4

9 COIL SPRING 2

14 STABILIZER BAR 1

GOAL: BUY PARTS TO

PRODUCE 200 CARS

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Motivation

Typical negotiation (sourcing) event in industrial procurement

PART DESCRIPTION UNITS

1 FRONT HUB 2

7 LOWER CONTROL ARM BUSHINGS

3

8 STRUT 4

9 COIL SPRING 2

14 STABILIZER BAR 1

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Motivation

Multi-item, multi-unit, multi-attribute negotiations in industrial procurement pose serious challenges to buying agents when trying to determine the best set of providing agents’ offers.

A buying agent’s decision involves a large variety of preferences expressing his business rules.

Providers require to express their business rules over their offering.

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Goal

To provide a negotiation service for buying agents to help them determine the optimal bundle of offers based on a large variety of constraints and preferences.

• assistance to buyers in one-to-many negotiations; and

• automated winner-determination in combinatorial auctions.

To relieve buying agents with the burden of solving too hard a problem (NP problem) and concentrate on strategic issues.

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Motivation

Requirements

Model

Implementation

Demo

Agenda

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Negotiation over multiple items. “Fuzzy” expressiveness to compose demands(e.g. quantity

requested per item lies within some range). Safety constraints. Establish minimum/maximum percentage of units

per item that can be allocated to a single provider. Capacity constraints. Allocated units cannot excede providers’

capacities. Item constraints. Capability of imposing constraints on the values a

given item’s attributes take on. Inter-item constraints. Capability of imposing relationship on different

items’ attributes.

RequirementsBuyer side

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Multiple bids/offers per provider Offers expressed over quantity ranges in batch sizes (e.g. Provider P

offers Buyer B from 100 to 200 3-inches screws in 25-unit buckets) Offers over bundles of items Types of offers over bundles

• XOR. Exclusive offers that cannot be simultaneously accepted.• AND. Useful for providers whose pricing expressed as a combination of

basis price and volumen-based price (e.g. Provider P’s unit price is $2.5 and different discounts are applied depending on volume of required items: 1-10 units (2%), 10-99 (3%), 100-1000 (5%)).

Homogeneous offers that enforce buyers to select equal number of units per offer item.

RequirementsProvider side

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Motivation & Goal

Requirements

Model

Agent Service Description

Demo

Agenda

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Modelled as a combinatorial problem defined as the optimisation(maximisation or minimisation) of:

• yj. (binary) decision variable on for the submitted bids• 0≤wj≤1 degree of importance assigned by the buyer to item i-th• V1, , ........ Vm bid valuation functions per item • qi

j decision variable on the number of units selected from j-th offer for i-th item

• pij unitary prices per item

• Δij = <δi1

j,…, δ ikj> bid values offered by j-th bid for i-th item

Realised as a variation of MDKP (multi-dimensional knapsack problem).

nj mi

ji

ji

jiiij pqVwy

1 1

),,(

Model

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SIDE CONSTRAINTS FORMALISATION

Units allocated to each provider falls within his offer

Allocated units per bid multiple of bid’s batch

Aggregation of selected bids’ units lies within requested ranges of units

Units allocated to a single provider do not exceed his capacity

Percentage of units allocated to a single provider does not exceed safety constraints

Model

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SIDE CONSTRAINTS FORMALISATION

Homogeneous combinatorial bids must be satisfied

Providers per item must comply with saftey constraints

AND bids must be satisfied

XOR bids must be satisfied

Intra-item constraints must be satisfied

Inter-item constraints must be satisfied

Model

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Motivation

Requirements

Model

Implementation

Demo

Agenda

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Service Architecture

RFQ

RFQ’RFQ’

RFQ’

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Service Architecture

PROPOSE (BIDS)

PROPOSE (BIDS)PROBLEM

SOLUTIONSOLUTION

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AUML Interaction protocol

Protocols implemented as

JADE behaviours (extensions of the

FSMBehaviour class)

IP-RFQ IP-CFP

IP Request Solution

IP-AWARD

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Service Ontology (I)RFQ

Buyer’s Constraints

ProviderResponse

Providers’ Constraints

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Service Ontology (II)

ProblemBid Solution

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Implementation features

All agents in the agency implemented in JADE FIPA as ACL (agent communication language) Two implementations of SOLVER

• ILOG CPLEX + SOLVER• MIP modeller based on GNU GLPK library

Ontology editor: Protegé2000 Ontology generator: The Beangenerator Protege2000

plugin to generate ready-to-use Java classes

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iBundler @ workBUYERTRANSLATOR

ProviderResponse

RFQ

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iBundler @ workTRANSLATOR BUYER

Problem

Solution

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Motivation & Goal

Requirements

Model

Agent Service Description

Demo

Agenda

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FRONT SUSPENSION, FRONT WHEEL BEARING

PART NUMBER

DESCRIPTION UNITS

1 FRONT HUB 2

7 LOWER CONTROL ARM BUSHINGS

3

8 STRUT 4

9 COIL SPRING 2

14 STABILIZER BAR 1

DemoParts acquisition

GOAL: BUY PARTS TO

PRODUCE 200 CARS

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iBUNDLER DEMO

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CONTRACT ALLOCATION

RFQ LINE

CONTRACTEE ALLOCATION

1 Alfa Ricambi

UK Parts Ltd.

50%

50%

2 Alfa Ricambi

GHL Motor

75%

25%

3 Alfa Ricambi

GHL Motor

8%

92%

4 UK Parts Ltd. 100%

5 UK Parts Ltd. 100%

DemoContract Allocation. Unconstrained RFQ

Unbalanced

allocation

Unsafe

allocation

Unsafe

allocation

Ignoring business rules may lead to inefficient allocations of products/services!!!

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DemoContract Allocation. Constrained RFQ

CONTRACT ALLOCATION

(CONSTRAINED)

RFQ LINE

CONTRACTEE ALLOCATION

1 Alfa Ricambi

UK Parts Ltd.

75%

25%

2 Alfa Ricambi 100%

3 Alfa Ricambi

GHL Motor

33%

67%

4 UK Parts Ltd.

GHL Motor

50%

50%

5 UK Parts Ltd.

GHL Motor

75%

25%

Balanced

allocation

Safe

allocation

Safe

allocation

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DemoConclusion

CONTRACT ALLOCATION

(CONSTRAINED)

RFQ LINE

CONTRACTEE ALLOCATION

1 Alfa Ricambi

UK Parts Ltd.

75%

25%

2 Alfa Ricambi 100%

3 Alfa Ricambi

GHL Motor

33%

67%

4 UK Parts Ltd.

GHL Motor

50%

50%

5 UK Parts Ltd.

GHL Motor

75%

25%

CONTRACT ALLOCATION

(UNCONSTRAINED)

RFQ LINE

CONTRACTEE ALLOCATION

1 Alfa Ricambi

UK Parts Ltd.

50%

50%

2 Alfa Ricambi

GHL Motor

75%

25%

3 Alfa Ricambi

GHL Motor

8%

92%

4 UK Parts Ltd. 100%

5 UK Parts Ltd. 100%

iBundler helps buyers & providers to reach better agreeements

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Summary and future works

iBundler is an agent-aware negotiation service to help buying agents to determine the optimal bundle of offers based on a large variety of constraints and preferences. It provides:

• assistance to buyers in one-to-many negotiations; and • automated winner-determination in combinatorial auctions.

What happens if all constraints cannot be met? Empirical evaluation of the agentified service vs web

service How to support bidders?

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Thank you ... Any questions?