Haul trucks queue at the shovel while the crusher sits starved. Road trucks idle in the yard waiting for a dock door. A railcar fleet that looked right on paper keeps missing the export window. Each of these problems is a fleet optimization problem, and each one costs money every shift it goes unsolved. Buying more equipment is the usual response, and it is often the wrong one.
MISIM helps mining and logistics operators answer fleet questions with evidence. Through its simulation consulting practice, MISIM builds models that show how many trucks, loaders, railcars or delivery vehicles an operation actually needs, how those units should be dispatched and maintained, and what each option is worth before capital is committed.
MISIM is based in North Vancouver, British Columbia, and works directly with owners and engineering teams on major capital and operating decisions around the world, for clients that include BHP, Vale, TotalEnergies and De Beers. Its team includes INFORMS Franz Edelman Award laureates whose modeling work has been credited with more than $300 million in client savings.
→ Is your next fleet purchase based on an average cycle time rather than how your operation really runs? Contact MISIM to discuss how fleet optimization can test the decision before the order is placed.
Why Do Fleet Optimization Decisions Go Wrong in Mines and Logistics Operations?
Most fleet decisions start with a calculation. A planning engineer takes the target tonnage or delivery volume, divides it by average cycle time and payload, adds a margin for availability and arrives at a fleet number. A mine planning package or an equipment vendor may refine the inputs, but the logic stays the same. On paper, the fleet works.
Then the fleet meets real conditions. Trucks bunch together after a shift change and arrive at the shovel in groups. A crusher outage backs up every loaded truck on the haul road. Haul distances grow as the pit deepens, so a fleet sized for year three is short by year six. At a distribution site, trucks arrive in a morning wave instead of evenly through the day, and the yard fills before noon. None of these events is rare, and none of them shows up in an average.
Fleets also share resources with everything around them. Haul trucks compete for loading units, dump points, fuel bays, maintenance bays and road space. Delivery vehicles compete for dock doors, yard slots and loading crews. When one part of the system slows down, the delay moves somewhere else, and the constraint that limits the fleet at 7 a.m. can be different from the one that limits it at 3 p.m.
The cost of getting fleet optimization wrong is large. Peer-reviewed research from McGill University’s Mining and Materials Engineering Department notes that loading and haulage account for about half of the operating costs of an open pit mine. The same study found that haul trucks in good working condition used roughly a third less fuel per tonne than the same models running in suboptimal condition, and that moving to larger trucks raised maintenance and fuel costs per tonne in the cases tested. Fleet size, fleet condition and fleet mix all move the numbers, and they interact with each other.
Undersize a fleet and the operation pays through lost tonnes, missed shipments and overtime. Oversize it and expensive equipment sits parked, tying up capital and often burning fuel in a queue. In both cases, the mistake usually becomes visible after the purchase order is signed. MISIM’s fleet optimization work is designed to find it earlier, while the decision can still change.
→ Are your trucks spending more time queuing than hauling? Contact MISIM to find out where your fleet is losing time and what it would take to recover it.
What Does Fleet Optimization Really Involve?
Fleet optimization means matching the number, type, deployment and upkeep of mobile equipment to what the operation has to deliver, at the lowest total cost and an acceptable level of risk. In practice, it covers several connected decisions.
Fleet size is the most visible one: how many haul trucks, loaders, road trucks, railcars or support vehicles the operation needs in each period. Fleet mix asks which equipment classes and payloads suit the haul profile, the loading units and the road network. Deployment covers dispatch logic, truck allocation between loading points, shift patterns and operating rules. Upkeep covers maintenance strategy, component replacement timing and the availability the fleet can realistically sustain.
These decisions depend on each other. A better dispatch rule can reduce the number of trucks required. A different maintenance policy can lift availability enough to defer a purchase. A larger stockpile ahead of the crusher can absorb variability that would otherwise call for spare trucks. Treating any one decision on its own risks solving the wrong problem.
That interdependence is why simulation, usually discrete event simulation, is the standard tool for serious fleet optimization. A simulation model follows each truck or vehicle through its cycle, including loading, hauling, dumping, queuing, refueling, breakdowns and shift changes, using distributions drawn from real operating data. Running the model many times produces a range of outcomes: a P10, P50 and P90 view of what a given fleet can deliver, along with the queues, utilization and idle time behind each result.
Fleet management and dispatch systems run today’s fleet well. They were built to execute a plan, though, and testing a different fleet size, haul network or rule set sits outside what they were designed to do. That gap is where MISIM concentrates its fleet optimization work.
→ Do you know how much production your current fleet can reliably deliver on a bad month? Contact MISIM to discuss a fleet optimization study that shows the full range of outcomes.
How Does MISIM Approach Fleet Optimization Differently?
MISIM builds fleet optimization studies to the standard required when a major equipment order, a life-of-mine plan or a long-term logistics contract depends on the answer. That standard shapes every engagement in five practical ways.
MISIM starts with the decision on the table
Every MISIM fleet optimization study begins with a specific question and the value at risk behind it. Should the mine buy six more trucks or fix the crusher feed? Can the current delivery fleet absorb 25% volume growth with a second shift? Does autonomous haulage reduce the fleet enough to justify the conversion cost? Framing the study around the decision keeps the scope focused and makes the outputs directly usable.
MISIM models the fleet inside the whole system
A fleet study that ignores the crusher, the stockpile or the dock doors gives a confident answer to the wrong question. MISIM models mobile equipment together with the fixed assets it serves, so shovel and truck matching, dump point congestion, crusher starvation and dock blocking all appear in the results. On integrated projects, MISIM has traced fleet requirements from the shovel face through processing and on to the rail terminal in a single model.
MISIM treats variability as the center of the problem
Breakdowns, weather, road conditions, operator differences and uneven arrivals are what make fleets underperform. MISIM represents each of them explicitly, then separates normal operating variability from project uncertainty so the financial case carries defensible ranges instead of one optimistic number.
MISIM validates before anyone relies on the results
A fleet model that has not been checked against real performance is a risk in its own right. MISIM compares model behavior with historical cycle times, production and availability, reviews the logic with the client’s operators and maintenance planners, and tests sensitive assumptions before presenting any scenario. This discipline is what makes a simulation model trustworthy enough to support capital decisions.
MISIM turns model output into decision evidence
Executives rarely need to see the model. They need to know how many units to buy, when to buy them, which operating changes to make first and how much risk the plan carries. MISIM translates fleet optimization results into fleet requirements by period, production ranges, trade-offs and inputs for the financial model.
→ Has a fleet study ever handed your team a single truck count with no view of the risk behind it? Contact MISIM to discuss fleet optimization that shows the expected outcome and the range around it.
Which Fleet Optimization Decisions Does MISIM Help Clients Test?
MISIM applies fleet optimization wherever mobile equipment moves material, product or people through constrained steps and the decision carries meaningful capital or operating cost. The most common applications follow.
Haul truck fleet sizing and shovel matching
For open pit and underground operations, MISIM tests how many trucks each loading unit needs as haul distances, ramp grades and dump destinations change across the mine plan. The model shows where trucks queue, where shovels wait and how fleet requirements shift between life-of-mine snapshots, so purchases can be timed to when extra capacity actually pays off. This work often sits inside broader mine value chain modeling, where hidden capacity elsewhere in the chain can reduce the need for new trucks.
Fleet replacement, autonomy and electrification
New equipment technology changes cycle times, fueling or charging patterns, traffic rules and availability. MISIM tests autonomous haulage, trolley assist and battery electric options against a validated model of the current fleet, so owners can see the production and cost effect before committing to a transition.
Dispatch and operating rules
Dispatch logic, truck allocation, shift change procedures, hot seating and fueling schedules can recover capacity without any new equipment. MISIM tests these rules side by side to show which ones raise production and which ones only move the queue.
Maintenance strategy and fleet availability
Maintenance policy decides how many trucks are available each shift. MISIM models planned and unplanned downtime, maintenance bay capacity and component replacement strategy so teams can compare the cost of more maintenance against the cost of more equipment.
Road truck and delivery fleets
At distribution centers, rail-connected logistics sites and terminals, truck fleets interact with gates, weigh scales, yards and dock doors. MISIM sizes delivery and shuttle fleets against realistic arrival patterns and loading times, an extension of its wider logistics simulation work.
Railcar and product transport fleets
For bulk supply chains running from mine to port, MISIM sizes railcar fleets, rake counts and concentrate trucking fleets against production, loadout capacity, port windows and weather disruption.
→ Is your team debating more trucks versus better dispatch without a fair way to compare them? Contact MISIM to test both options against the same baseline.
How Does MISIM Fleet Optimization Work With Your Existing Platforms?
Mining and logistics operators already run a stack of systems that track their fleets. Mine fleet management and dispatch systems record every load, cycle and delay. Telematics and GPS platforms log location, speed and idle time. A CMMS or the maintenance module of an ERP holds failure and repair histories. Mine planning software holds haul profiles and production schedules. On the logistics side, transportation, yard and warehouse management systems capture arrivals, dwell times and loading activity, and Power BI or Tableau dashboards sit on top of much of it. MISIM does not ask clients to replace any of these platforms.
MISIM uses them as the data foundation for fleet optimization. Dispatch records set cycle time and queue distributions. Telematics data shows real travel speeds and idle patterns by road segment. Maintenance histories define how reliable each equipment class is. Planning data sets the haul network for each future period. The simulation model then shows something none of those systems can show alone: how the whole fleet and the assets around it behave when conditions change.
Results flow back in forms that fit existing processes, including fleet requirements by year for the capital plan, production ranges for the financial model and scenario comparisons for dashboards. Where a client wants ongoing support, MISIM can connect the model to operational data as a simulation-based digital twin for repeated planning use.
This is also why MISIM works as a consulting partner rather than a software vendor. A fleet optimization model only helps when it reflects how a particular site actually operates, and that takes engineers who understand the operation as well as the modeling.
→ Does your dispatch system hold years of data that has never been used to test a fleet decision? Contact MISIM to discuss how fleet optimization can turn that data into evidence.
What Does a MISIM Fleet Optimization Engagement Look Like?
MISIM keeps engagements focused and collaborative. The owner team brings the decision context, mine plans or site layouts, engineering inputs, operating data and subject matter expert review. MISIM brings the model structure, the treatment of variability and uncertainty, scenario design, validation and analysis. Together they produce fleet requirements, production ranges, trade-offs, risks and financial model inputs.
Most projects follow a clear sequence. MISIM and the client agree on the decision and how success will be measured, build the model, confirm it reproduces known performance, test the fleet options that matter and present findings in terms leadership can act on. MISIM formalizes this sequence in its DIVES methodology, and the stages are set out on its how it works page.
Scope matches the question. A focused study on truck count for a single pit, or delivery fleet sizing for one facility, may take a few weeks. A fleet optimization study covering several life-of-mine periods, a mine-to-port corridor or a greenfield project takes longer and often runs in phases tied to project gates. MISIM also supports engineering firms and owners during feasibility, design and sanction, when changing direction is still inexpensive. For many teams, fleet work becomes one part of wider scenario planning with simulation across the operation.
→ Approaching a feasibility gate or an equipment order with fleet assumptions nobody has tested? Contact MISIM to scope a study that fits your project timeline.
Which Industries Rely on MISIM for Fleet Optimization?
The equipment varies by sector, but the pattern of queues, shared resources and variability stays the same. MISIM focuses its fleet optimization work where that pattern carries the most capital risk.
Mining
Open pit and underground mines use MISIM to size haul and loading fleets, compare equipment classes, test ramp-up and plan fleet growth across the life of the mine. MISIM links these fleet decisions to achievable production ranges that feed valuation and sanction decisions.
Oil and gas
Oil sands mining and other large oil and gas operations run truck and shovel fleets that must stay matched to processing capacity. MISIM models these fleets alongside the plant so maintenance strategy and fleet availability are tested against end-to-end performance.
Ports and terminals
Terminal tractors, yard trucks and external truck arrivals all affect berth and yard productivity. MISIM tests fleet levels and gate arrangements against vessel schedules and storage capacity.
Rail
MISIM sizes railcar fleets, rakes and locomotives against loadout capacity, cycle times and delivered tonnage targets across the rail haul.
Warehousing and logistics
Distribution and logistics operators use MISIM to size delivery fleets, shuttle trucks and yard equipment against dock capacity and realistic demand, often alongside warehouse optimization work inside the building.
MISIM’s case studies show the range of operations the team has modeled. Although MISIM is headquartered in North Vancouver, it works with owners and engineering teams on mining and logistics decisions on several continents.
→ Does your operation run a fleet that generic planning tools were never built to model? Contact MISIM to discuss a fleet optimization study built around how your site actually runs.
How Do MISIM Model Audits and Custodianship Keep Fleet Models Reliable?
A fleet model delivers its first value when the original decision is made, and the operation keeps changing after that. Haul roads lengthen, equipment ages, volumes grow and dispatch rules shift. A model that is not maintained drifts from reality, and fleet decisions made on an outdated model carry hidden risk.
MISIM addresses this through two related services. Model audits review existing simulation and fleet models, whether built by MISIM, an internal team or another provider, to check assumptions, logic and data before they inform a new purchase. An audit is often the quickest way to learn whether a fleet model already on file can be trusted for the next equipment decision.
Model custodianship provides ongoing governance, updates and validation so a fleet model stays accurate as the operation changes. For operators who revisit fleet requirements every budget cycle, custodianship turns one study into a planning asset that supports optimizing resource allocation year after year, and it connects directly to MISIM’s work on de-risking capital investment decisions.
→ Is your fleet model older than your current mine plan? Contact MISIM to discuss an audit before it shapes your next equipment order.
Why Choose MISIM for Fleet Optimization?
Mobile equipment is one of the largest capital and operating costs in mining and logistics, and fleet decisions are hard to reverse once equipment arrives on site. Fleet optimization gives leadership a tested view of how many units the operation needs, how to run them and what each option is worth.
MISIM combines validated simulation, an integrated view of fleets and the assets they serve, and a consulting team with decades of experience in complex industrial systems. Whether the question is truck count, dispatch rules, electrification or a delivery fleet, MISIM helps your team make the call with evidence.
Contact MISIM to discuss the fleet decision in front of your team.
MISIM Fleet Optimization: FAQs
What fleet optimization questions does MISIM answer?
MISIM answers questions about fleet size, fleet mix, dispatch and allocation rules, maintenance strategy, equipment replacement and technology transitions such as autonomous or battery electric haulage. Typical examples include how many haul trucks a mine needs in each period of the mine plan, whether better dispatch can defer a purchase and how many delivery trucks a logistics site needs to meet peak volumes. If the answer depends on how equipment interacts with shared resources under variability, it is a strong fit.
How is MISIM fleet optimization different from a spreadsheet fleet calculation?
A spreadsheet divides target volume by average cycle time and adds a margin. MISIM’s simulation follows each vehicle through loading, hauling, queuing, breakdowns and shift changes, so it captures the bunching, congestion and downtime that averages hide. The output is a range of production outcomes for each fleet option, with the queues and idle time behind them, which gives capital planning teams a known level of confidence.
Does MISIM replace our fleet management or dispatch system?
No. MISIM uses data from fleet management, dispatch, telematics and maintenance systems to build and calibrate the model, then returns results that feed capital plans, financial models and dashboards. Your dispatch system keeps running the fleet day to day, while MISIM’s model tests what happens if the fleet or the operating rules change. Many clients already hold enough data to start a study without new collection.
How does MISIM validate a fleet optimization model before it informs a capital decision?
MISIM compares model results with historical cycle times, production, queue behavior and equipment availability, reviews the logic with operators and maintenance planners and tests how sensitive the results are to key assumptions. Clients see the validation evidence, so they know how far the model can be trusted and where its limits sit.
Can MISIM help us evaluate autonomous or electric haul fleets?
Yes. MISIM models how autonomous haulage, trolley assist and battery electric trucks change cycle times, traffic rules, charging or fueling demand and availability. The comparison runs against a validated model of the current fleet, so owners see the production and cost effect of the transition before committing capital.
How long does a MISIM fleet optimization project take?
A focused study for one pit or one logistics facility can take a few weeks. Studies covering several life-of-mine periods, a mine-to-port corridor or a greenfield project take longer and are often phased around project gates. MISIM sets scope and timing during the first conversation, based on the decision and the value at risk.
Which industries does MISIM support with fleet optimization?
MISIM supports mining, oil and gas, ports and terminals, rail, and warehousing and logistics operations. The common thread is a large operation where mobile equipment interacts with fixed assets and a fleet decision carries significant capital or production risk.
What does MISIM need from our team to start a fleet optimization study?
MISIM needs a clear decision to support, mine plans or site layouts, fleet and dispatch data, maintenance records and access to the people who know how the operation really runs. MISIM handles model structure, validation, scenario design and analysis from there. Where data is incomplete, MISIM documents reasonable assumptions and tests how much they affect the results.
