ict 1 a heuristic for maritime inventory routing oddvar kloster, truls flatberg molde, 2009-09-22
TRANSCRIPT
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ICT 1
A heuristic for maritime inventory routing
Oddvar Kloster, Truls Flatberg
Molde, 2009-09-22
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ICT 2
Overview
Background Model Algorithms Test example
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ICT 3
Invent
Software library to solve generic Inventory Routing Problems Primary focus on routing and inventories Upstream/downstream activity disregarded Contractual and economic aspects Tramp shipping, industrial shipping and combinations
Prototype with initial construction algorithm, genetic algorithm and nascent optimization
Three applications used as pilot studies Cement - multiple products, short horizon, no spot Chemical tankers - tramp and inventory, multiple products, cleaning, tank
handling LNG - single product, long term, contracts, full loads
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ICT 4
Model features (1)
Heterogeneous vessels One or more tanks with volume capacities Or, simple stowage (max products)
Ports, with storages Variable production/
consumption rates Partly interruptible Storage capacities
Per-vessel time/distance/cost table
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ICT 5
Model features (2)
Multiple products Keep track of quantity, weight and volume Fixed or variable densities Cleaning of tanks between products
Load and discharge rates Boil-off
Product evaporates during sailing
Full vessel loads Leave from production ports with full loads Discharge completely in consumption port except for boil-off needs
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ICT 6
Model features (3)
Bookings Transportation demands not related to storages
Contracts Limit amount delivered to certain ports in certain periods Define prices
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ICT 7
Model features (4)
Priority on storages and contracts Arrival and departure load limits (draft restrictions) Port closure periods Vessel maintenance periods Vessel-port compatibility Restrict # visits to storage in period Inter-arrival gaps
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ICT 8
Plan structure
ActionVessel
Port stayPort Storage
Port Booking
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ICT 9
Objectives
Basic objectives Income (contract, stream, booking) Cost (sailing, port stay, cleaning) Performance (quantity transported) Penalized constraints
Combined objectives Weighted sum Lexical (prioritized)
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ICT
Solution strategy
Work with concrete plans Violate constraints by doing too little → penalize
Stockout/overflow Unserviced booking Contract limit not met Too few visits in time period
Add activities, as efficiently as possibly When doing too much, try delaying
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ICT 11
Construction: overview
Start with empty plan Identify earliest (highest priority) penalty event
Stockout/overflow Unserviced booking Contract limit Too few visits in time period
Generate journeys Rank journeys Add best journey and repeat If no fix found, forget event … until there are no more penalty events
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ICT 12
Construction: journey generation
One storage/booking/contract given Choose
(Contract) Counterpart storage (Counterpart contract) Vessel Insertion points
P1
P2
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ICT 13
Construction: journey insertion
Large parts of the plan may be affected Schedule for selected vessel changes after new load action Schedules for other vessel are unchanged Schedules may change for storages visited by selected vessel
Many constraints to satisfy Roughly:
Assume small quantity and propagate time Find maximum possible quantity (including tank allocation) Set quantity, propagate time and quantities Insert tank cleaning actions Check feasibility If necessary, delay and repeat
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ICT 14
Construction: journey ranking
Evaluate criteria for each journey Transport large quantity Short sailing time Large quantity/vessel capacity Large quantity/sailing time Low cost/quantity ... Random
Sort journeys for each criterion Final score is weighted sum of ranks
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ICT 15
Genetic algorithm
Population of individuals Each individual’s genome is a set of weights Fitness of each individual is evaluated by
applying the construction algorithm Weights for new individuals drawn around
parents’ weights (+ mutation)
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ICT 16
Optimization
Remove a bit of the solution Any journey starting or ending in
random (~10%) interval Compact solution Regenerate the missing part
Use criteria weights from the bestGA individuals
Accept if better or promising Avoid known solutions
by objective value
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ICT
Test case
LNG. 1 product, boil-off, full loads 2 production ports
Fixed purchase price Fixed production rate
2 consumption ports Some interruption allowed Fixed sales price on send-out
3 identical vessels 360 day horizon
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ICT 18
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ICT 19
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ICT 20
Example run (GA)
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ICT 21
Example run (optimization)
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ICT 22
A heuristic for maritime inventory routing
Oddvar Kloster, Truls Flatberg
Molde, 2009-09-22