Inventory routing problems - Combined inventory management and routing Henrik Andersson Arild Hoff Marielle Christiansen Geir Hasle Arne Løkketangen.

Inventory routing problems- Combined inventory management and routing

Henrik AnderssonArild Hoff

Marielle ChristiansenGeir Hasle

Arne Løkketangen

DOMinant workshop - Molde - September 20-22 2009

Outline

• Background• Industrial aspects• Literature review and classification• Industrial aspects in the literature• Trends and future directions

Background

• DOMinant is a collaboration between Molde University College, Norwegian University of Science and Technology and SINTEF

• Discrete optimization models in maritime and road-based transportation– Fleet size and mix vehicle routing problem– Inventory routing problem

• First task : Get familiar with the research and write a survey on each problem



Surveys

• Focused surveys with a broader purpose– Overview of the diverse landscape of combined inventory

management and routing – Relation and interconnection between science and practice– Practitioners can see the benefit of using advanced decision support

systems in complex situations– Inspire researchers to dig deeper into the field and find new and

exciting challenges– Discuss both land-based and maritime applications

• Mainly based on the research literature – Own experience– No field study or industry involved in the writing process


Combining operations I

• Combining operations within the supply chain– Increased efficiency– Economical benefits– Flexibility in services– Improved robustness

• Which operations to integrate?• Who should plan the integrated operations?• For which products is it interesting to integrate operations?• When should operations be integrated?


Combining operations II

• Which operations to integrate?– Inventory ≈ A buffer between processes to even out variations and

handle uncertainty– Managing the conflicting goal between supply and demand

• Procurement – Inventory – Production (intra)• Production – Inventory – Sales (intra)• Inventory – Transportation – Inventory (intra and inter)

Supply

Demand


Combining operations II

• Which operations to integrate?– Inventory ≈ A buffer between processes to even out variations and

handle uncertainty– Managing the conflicting goal between supply and demand

• Procurement – Inventory – Production (intra)• Production – Inventory – Sales (intra)• Inventory – Transportation – Inventory (intra and inter)

Supply

DemandInventory


Motivation

Producer

Supplier Customer

Customer

Customer

Customer

Producer

Producer

Supplier


Motivation

Producer

Supplier Customer

Customer

Customer

Customer

Producer

Producer

Supplier

Control Execute


Motivation

• Economical benefits• Flexibility in services• Improved robustness

Producer

Supplier Customer

Customer

Customer

Customer

Producer

Producer

Supplier

ControlExecute

Combining operations III

• Who should plan the integrated operation?– The producer– A transport provider– A third actor



Combining operations IV

• For which products is it interesting to integrate operations?– High value products– Perishable products– High impact products


Combining operations V

• When should operations be integrated?– Autonomous actors in the chain• Economically beneficial at the system level• Possible to split the benefits in an agreeable way• Long-term relationship• Willingness to share information and data


Current industrial practice

• Inventory management and routing are treated as separate operations– manual planning is still used at many companies

• There are very few, if any, commercial optimization-based systems in current use

• Several integrated systems are under development for companies in the maritime sector– The liquefied natural gas industry mainly due to an

extraordinary strong growth in this high value business


Research perspective

• Looking at the coordination of inventory management and routing, it is clear that the combined problem is a long-term, dynamic problem that is inherently stochastic

• Since long-term, dynamic and stochastic problems are extremely difficult to solve, the approaches found in the literature have simplified the problem in one way or another


ClassificationCharacteristic Alternatives

Time Instant Finite Infinite

Demand Deterministic Stochastic

Topology One-to-one One-to-many Many-to-many

Routing Direct Multiple Continuous

Inventory Fixed Stock-out Lost sale Back-order

Fleet Homogeneous Heterogeneous

Fleet size Single Multiple Unconstrained

Mode Road-based Maritime Generic

Finite

• More than one visit at a customer may be needed

• Common characteristics– Deterministic demands– Fixed inventory restrictions

• Road-based, maritime and generic– Many-to-many topology without depot– Few deliveries– Heterogeneous fleet



Finite II

• Very few exact approaches– Christiansen and Nygreen, 2005 • Robust plans, penalize closeness to inventory limits• Path-based formulation• Branch-and-price

– Archetti et al., 2007• Order-up-to-level policy, one vehicle• Arc-flow formulation• Branch-and-cut


Finite III

• MP-based and neighborhood-based heuristics– Arc-flow

• Miller, 1987 ; Al-Khayyal and Hwang, 2007 ; Savelsberg and Song, 2008 ; Yugang, 2008

– Path-flow• Bell et al., 1983 ; Persson and Göthe-Lundgren, 2005

– Neigborhood-based• Rusdiansyah and Tsao, 2005 (Tabu search) ; Abdelmaguid

and Dessouky, 2006 (GA) ; Alegre et al., 2007 (Scatter search) ; Dauzère-Pérès, 2007 (Memetic) ; Savelsbergh and Song, 2007 (GRASP) ; Hemmelmayr et al., 2008 (VNS)


Finite IV

• Heuristics : Main approaches– Allocate first – route second• Carter et al., 1996 ; Campbell and Savelsbergh, 2004

– Periodic and delivery patterns• Gaur and Fisher, 2004 ; Rusdiansyah and Tsao, 2005 ;

Alegre et al., 2007

– Imposing different inventory policies• Kim and Kim, 2000 ; Bertazzi et al., 2002


Industrial aspects I

• Products having a relatively high consumption rate.– Gas, Bell et al., 1983, Golden et al., 1984, Campbell and

Savelsbergh, 2004 ; chemicals, Miller, 1987 ; automobile components, Blumenfeld et al., 1987, Alegre et al., 2007 ; ammonia, Christiansen, 1999 ; groceries, Gaur and Fisher, 2004 ; bitumen, Persson and Göthe-Lundgren, 2005 ; frozen products, Custódio and Oliveira, 2006 ; calcium carbonate slurry, Dauzère-Pérès et al., 2007 ; petrochemical products, Al-Khayyal and Hwang 2007 ; blood, Hemmelmayr et al., 2008


Industrial aspects II

• The uniqueness of the industrial cases is important– Factors not included in already existing models

• Can either complicate or sometimes simplify the problem

• Knowledge about the number of customers that are normally visited on a route to simplify the generation of routes

• Using the consumption/production rates and inventory bounds to explicitly model each possible port call and to derive time windows for each visit

• Characteristics from the current manual planning


Industrial aspects

• Most research where industrial problems are focused holds elements of heuristics– Exact methods terminated prematurely– Neighborhood-based heuristics and metaheuristics

• The diversity of methods used shows many paths for designing algorithms for industrial cases

• Knowledge about the case, and the delicate use of this knowledge when formulating and solving the problem shines through in most applications


Status summary

• Gain in interest due to increased focus on supply chain management

• Many different problems, no clear definition• A gap between research and academia• Little work on exact methods


Trends in industry

• Data availability, visibility and information sharing

• Increased cooperation along the supply chain• Increased globalization• Acquisitions and mergers• Extended transport contracts, 3PL, 4PL• A number of DSSs under development• Environmental focus


Trends in the research literature

• Richer models• Uncertainty and risk• Industrial cases• Advanced heuristics


Future research directions

• Richer models and integrated systems• Focus on uncertainty, robustness and

flexibility• From cost minimization to profit maximization• Better benchmarks

Inventory routing problems - Combined inventory management and routing Henrik Andersson Arild Hoff Marielle Christiansen Geir Hasle Arne Løkketangen.

Documents

supply demand inventory

integrated operations

supply demand slide

background dominant

molde university college

routing relation

supply chain

research literature