TMS Route Optimization: A Practical Guide for Transport Professionals

‍Route optimization software: Due to the fact that plans are subject to suddenchanges.

No plan isever really final in the world of logistics. Every minute, customer demandschange, drivers shift, and vehicles break down. Being prepared to actimmediately is essential to staying ahead.

CADIS makes that possible with routeoptimization software, a next-generation feature built to deliver agility underpressure.

Flexibilitybecomes more than just a benefit when logistics operatiOptimisation des tournées TMS : guide pratique pour les professionnels du transport L’optimisation des tournées dans un TMS consiste à planifier les livraisons et les enlèvements en tenant compte non seulement de la distance, mais aussi des capacités des véhicules, des contraintes opérationnelles, des horaires et des règles de dispatching.

Dans les opérations de transport réelles, trouver le trajet le plus court ne suffit pas. Le véritable objectif est de construire des tournées efficaces qui puissent effectivement être exécutées.

Qu’est-ce que l’optimisation des tournées dans un TMS ?

L’optimisation des tournées permet à un Transportation Management System de calculer une organisation efficace des expéditions, enlèvements, véhicules et arrêts.

Selon l’exploitation, les objectifs peuvent notamment être de :

• réduire la distance totale parcourue ;
• réduire le temps de conduite ;
• améliorer l’utilisation des véhicules ;
• limiter le nombre de tournées nécessaires ;
• respecter les contraintes de livraison et d’enlèvement ;
• déterminer une séquence d’arrêts réaliste.

Le mot clé est réaliste.

Une solution d’optimisation doit trouver une organisation efficace dans les contraintes de l’exploitation, et pas seulement dessiner un itinéraire sur une carte.

Planification de tournée, optimisation de tournée et optimisation de séquence

Ces trois concepts ne doivent pas être confondus.

Planification de tournée
Détermine quels transports doivent être regroupés dans une tournée.

Optimisation de tournée
Recherche une combinaison efficace de livraisons, enlèvements et véhicules en fonction des paramètres définis.

Optimisation de séquence
Détermine dans quel ordre les différents arrêts d’une tournée doivent être exécutés.

Dans une exploitation mature, ces trois étapes sont généralement liées.

Quelles données sont nécessaires pour optimiser efficacement les tournées ?

La qualité du résultat dépend directement de la qualité des données disponibles.

Données relatives aux expéditions et enlèvements

Le système doit connaître les transports qui doivent être exécutés ainsi que les informations nécessaires à leur planification.

Géolocalisation fiable

Une adresse incorrecte ou non géocodée peut empêcher ou dégrader une optimisation.

Dans CADIS, les adresses peuvent être géocodées et corrigées lorsque les informations géographiques nécessaires ne sont pas disponibles.

Informations sur les véhicules

Une optimisation réaliste doit également tenir compte des caractéristiques du parc.

Dans l’optimisation de tournées CADIS, les véhicules peuvent notamment être différenciés selon des caractéristiques telles que :

• charge utile ;
• emplacements palettes ;
• équipement pour marchandises dangereuses ;
• hayon élévateur.

Contraintes temporelles

Les horaires et restrictions de livraison influencent directement la faisabilité d’une tournée et l’ordre optimal des arrêts.

Comment fonctionne concrètement une optimisation de tournées ?

1. Définir ce qui doit être optimisé

Il n’est pas toujours nécessaire d’optimiser l’ensemble des transports.

Selon le contexte opérationnel, il peut être plus pertinent de travailler sur une sélection d’expéditions et d’enlèvements.

2. Définir les ressources disponibles

Le planificateur doit ensuite préciser les véhicules ou types de véhicules pouvant être utilisés.

CADIS permet de travailler avec des véhicules individuels ou avec un nombre défini de véhicules par type.

3. Définir les objectifs de planification

Une entreprise peut, par exemple, chercher à créer le moins de tournées possible ou à utiliser un parc de véhicules disponible d’une certaine manière.

Les objectifs doivent correspondre aux priorités opérationnelles réelles.

Il est également prudent de ne pas planifier systématiquement les véhicules à 100 % de leur capacité théorique lorsque les données de volume ou de chargement comportent une marge d’incertitude.

4. Calculer avant d’appliquer

Une bonne optimisation ne doit pas modifier immédiatement l’exploitation.

Dans CADIS, les calculs d’optimisation peuvent être effectués et examinés avant que le résultat ne soit appliqué.

Plusieurs scénarios peuvent ainsi être calculés puis comparés.

Parmi les résultats pouvant être examinés figurent notamment :

• nombre de tournées ;
• durée totale de conduite ;
• distance totale ;
• véhicules utilisés ;
• expéditions et enlèvements planifiés ou non planifiés.

5. Vérifier le résultat d’un point de vue opérationnel

Un résultat mathématiquement efficace n’est pas nécessairement le meilleur résultat pour l’exploitation.

Le planificateur doit notamment vérifier :

• si tous les transports importants sont planifiés ;
• si l’utilisation de capacité est réaliste ;
• si certaines tournées sont disproportionnées ;
• si les contraintes opérationnelles ont été correctement prises en compte.

6. Appliquer la solution choisie

Ce n’est qu’après validation que le résultat doit devenir opérationnel.

Dans CADIS, l’application du résultat crée les tournées correspondantes et affecte les expéditions et enlèvements planifiés.

L’optimisation des tournées n’est qu’une partie du processus

Dans une organisation de transport réelle, une autre question est souvent encore plus importante :

Comment les expéditions arrivent-elles dans la bonne tournée avant l’optimisation ?

C’est là qu’interviennent le dispatching, les règles de planification et les modèles de tournées.

Du routage au dispatching automatique

Lorsque les volumes augmentent, le dispatching entièrement manuel devient difficile à maintenir.

CADIS peut utiliser différentes informations pour affecter les expéditions aux tournées, notamment :

• zones de codes postaux ;
• routes prédéfinies ;
• données transmises par un système amont ;
• caractéristiques des expéditions ;
• règles de dispatching.

Dans cadisSTUDIO, le moteur de règles permet de définir des règles de dispatching détaillées et de les simuler avant leur utilisation.

Cela permet de combiner deux approches complémentaires :

Les règles traduisent la connaissance opérationnelle.
L’optimisation recherche ensuite une solution efficace dans ce cadre.

Utiliser des tournées récurrentes sans perdre en flexibilité

De nombreux réseaux de transport utilisent des tournées régulières.

Dans ce cas, il n’est pas nécessaire de reconstruire l’ensemble du plan chaque jour.

CADIS permet de travailler avec des modèles de tournées pour les opérations Last Mile et Line Haul.

Ils peuvent définir, entre autres :

• la tournée ;
• les jours d’exécution ;
• le véhicule ;
• certaines caractéristiques opérationnelles.

La structure récurrente peut ensuite être combinée avec le dispatching et l’optimisation.

Pourquoi l’optimisation de séquence reste importante

Même lorsque les expéditions ont déjà été affectées à une tournée, l’ordre des arrêts peut encore être amélioré.

Dans cadisSTUDIO, l’optimisation de séquence peut être utilisée pour les tournées First Mile et Last Mile.

Elle peut notamment être exécutée avant le chargement afin de déterminer une séquence adaptée, ou être recalculée pour les arrêts encore non exécutés.

Le système peut ensuite mettre à jour la séquence ainsi que les heures prévues d’arrivée et de départ.

Sept erreurs fréquentes dans l’optimisation des tournées

1. Optimiser avec de mauvaises données

Une adresse incorrecte, une capacité erronée ou une information manquante peut conduire à un mauvais résultat.

2. Planifier systématiquement à 100 % de capacité

Une utilisation maximale théorique laisse peu de marge pour les variations opérationnelles.

3. Se concentrer uniquement sur les kilomètres

Le kilométrage n’est qu’un indicateur parmi d’autres.

Le temps de conduite, le nombre de véhicules, les contraintes horaires et la faisabilité sont également importants.

4. Sous-estimer la géolocalisation

Sans données géographiques fiables, même un bon algorithme d’optimisation ne peut pas produire un résultat fiable.

5. Essayer de remplacer complètement l’expérience du dispatcher

L’optimisation fonctionne mieux lorsque les règles opérationnelles sont correctement représentées dans le système.

6. Appliquer automatiquement chaque calcul

La possibilité de comparer plusieurs scénarios avant de les appliquer donne au planificateur davantage de contrôle.

7. Séparer la planification de l’exécution

Une tournée optimisée n’apporte de valeur que lorsqu’elle peut être transférée efficacement vers les étapes suivantes de l’exploitation.

Checklist pour choisir une solution de TMS route optimization

Avant de choisir une solution, vérifiez si elle peut :

• traiter simultanément livraisons et enlèvements ;
• prendre en compte différents types de véhicules ;
• gérer les contraintes de capacité ;
• intégrer les restrictions temporelles ;
• optimiser seulement une partie des transports si nécessaire ;
• comparer plusieurs scénarios ;
• afficher les résultats au niveau des tournées et des arrêts ;
• optimiser la séquence d’une tournée existante ;
• gérer les problèmes de géocodage ;
• intégrer des règles de dispatching ;
• travailler avec des modèles de tournées récurrentes ;
• recevoir des informations de systèmes amont ;
• connecter la planification à l’exécution opérationnelle.

Comment CADIS s’intègre dans ce processus

CADIS couvre plusieurs étapes successives du processus de planification et d’exécution du transport :

Données d’expédition et d’enlèvement → Routage et règles de dispatching → Création des tournées → Optimisation → Optimisation de séquence → Chargement → Exécution par le conducteur

L’optimisation de tournées décrite dans la documentation CADIS fait partie de cadisCONTROL, tandis que cadisSTUDIO propose notamment des fonctions complémentaires de données de base, de règles, de modèles de tournées et d’optimisation de séquence.

L’objectif n’est donc pas uniquement de calculer une route, mais de relier la planification aux processus opérationnels qui suivent.

Quand l’optimisation des tournées devient-elle particulièrement intéressante ?

Elle est particulièrement pertinente lorsque l’exploitation doit gérer :

• des volumes variables ;
• des livraisons et des enlèvements ;
• plusieurs types de véhicules ;
• différentes contraintes de capacité ;
• des horaires de livraison ;
• des modifications fréquentes du plan ;
• une charge de travail importante liée au dispatching manuel.

Plus le nombre de contraintes augmente, plus il devient difficile de construire manuellement un plan cohérent.

Conclusion : optimiser l’exploitation, pas seulement l’itinéraire

Une bonne optimisation de tournées ne consiste pas simplement à trouver le trajet le plus court.

Elle doit combiner les commandes, les véhicules, les règles métier, les contraintes temporelles et l’exécution réelle.

C’est également là que se situe la différence entre un outil de routage isolé et une solution intégrée au processus de transport.

Vous souhaitez évaluer comment CADIS pourrait prendre en charge votre processus de planification, de dispatching et d’optimisation des tournées ?

Contactez CADIS pour discuter de votre environnement de transport et de vos exigences opérationnelles.

ons are conducted inreal time; it becomes essential for survival. By enabling dispatchers andplanners to dynamically reassign vehicles, CADIS makes sure that no shipmentpauses, even in the event of an unforeseen circumstance.

FlexibilityUnder Duress

Let's sayyour driver's car breaks down in the middle of a delivery route. This used toset off a series of phone calls, rescheduling, and delays. This becomes aprecise, real-time logistics operation with little downtime when using CADIS.

Dispatcherscan quickly switch a whole trip to another available vehicle by using routeoptimization software. The new assignment is automatically followed by allrelated data, such as stop sequence, load information, and route optimization.The CADIS mobile app instantly provides the driver with the most recent tripinformation, guaranteeing a smooth delivery process.

Theoutcome? No time lost. No mayhem. Just efficient, flexible logistics thatmaintain customer satisfaction and operational efficiency.

Map with aLive Vehicle SwitchTMS Route Optimization: A Practical Guide for Transport Professionals

Route optimization sounds simple: find the shortest or fastest way to visit a set of stops.

In real transport operations, it is rarely that simple.

A dispatcher does not plan dots on a map. They plan deliveries and collections with different priorities, vehicle capacities, equipment requirements, time restrictions and operational constraints. And once the plan is ready, somebody still has to assign the shipments, prepare the vehicle, communicate the trip to the driver and react when reality changes.

That is why TMS route optimization should not be viewed as an isolated routing algorithm. Its real value comes from connecting optimization with the wider transportation workflow.

This guide explains what logistics professionals should expect from route optimization within a Transportation Management System (TMS), which data matters, where optimization projects commonly fail and how solutions such as CADIS approach the process from planning through execution.

What is TMS route optimization?

TMS route optimization is the process of using transportation data, operational constraints and optimization logic to build more efficient transport plans.

Depending on the operation, the objective may be to:

• reduce total driving distance,
• reduce driving time,
• improve vehicle utilization,
• use fewer vehicles,
• meet delivery and collection requirements,
• create feasible stop sequences,
• or balance several of these objectives simultaneously.

The important word is feasible.

The mathematically shortest route is not necessarily the route a transport company can actually execute.

A route might look efficient on a map but fail operationally because the vehicle does not have enough payload, a shipment needs equipment that the vehicle does not have, a customer must be reached within a certain time window or the stop data is incomplete.

For transport professionals, good optimization therefore means:

Finding an efficient plan within the constraints of the real operation — and making that plan executable.

Route optimization vs. simple route planning

Basic route planning answers a relatively straightforward question:

In which order should these stops be visited?

A more complete TMS route optimization process can answer a broader question:

Which shipments and collections should be assigned to which routes and vehicles, and in which sequence should those stops be executed?

That distinction matters.

There are typically two optimization levels in transport planning.

1. Route or trip creation

The system determines how shipments and collections should be distributed across available routes or vehicles.

This is where fleet size, vehicle type and capacity become important.

2. Stop sequence optimization

Once a trip exists, the system determines the most appropriate order of its stops.

This can also be useful later in the operation. For example, if an additional collection is assigned to an existing trip, the remaining stops may need to be optimized again.

A mature TMS should support both workflows rather than treating routing as a one-time calculation.

The data that determines whether route optimization works

Optimization quality depends heavily on input quality.

Before discussing algorithms, transport companies should evaluate whether their operational data is complete enough to produce reliable results.

Shipment and collection data

The optimizer needs to know what must be transported.

Depending on the operation, relevant information can include:

• delivery and collection addresses,
• execution dates,
• shipment characteristics,
• weights and capacities,
• service requirements,
• time restrictions,
• and other planning-relevant properties.

Missing or inaccurate shipment data can make a technically correct optimization operationally unrealistic.

Geocoding

Optimization requires usable geographical coordinates.

An address that humans understand perfectly may still be ambiguous for a routing engine.

This is why geocoding should be part of the planning workflow rather than treated as an unrelated data-cleaning exercise.

In CADIS, planners can identify shipments with missing geographical information and geocode them. Address candidates can be evaluated and, when necessary, locations can be adjusted manually on the map.

This matters because poor geographical data does not simply reduce optimization quality. In some cases, it can prevent optimization altogether.

Vehicle data

Not every shipment can travel on every vehicle.

Relevant vehicle characteristics can include:

• payload,
• pallet capacity,
• equipment for dangerous goods,
• tail lift availability,
• and other fleet characteristics.

A useful optimizer therefore needs information about both the transport demand and the resources available to execute it.

Time restrictions

Transport operations often involve delivery or collection windows.

An optimized sequence must therefore consider not only distance but whether stops can realistically be reached at acceptable times.

This is an important distinction between a route that looks good on a map and a route that works in daily operations.

A practical TMS route optimization workflow

The following workflow provides a useful framework when evaluating or implementing route optimization.

Step 1: Define what should be optimized

Optimization does not always need to include every open shipment.

A dispatcher may want to optimize:

• all shipments and collections for a planning period,
• a particular geographical area,
• a shipment group,
• or only a selected set of orders.

CADIS supports route optimization for both broader planning sets and selected shipments and collections.

This gives planners an important level of control: optimization can support the dispatcher's workflow rather than forcing every planning situation into the same process.

Step 2: Define the fleet available for the calculation

The optimization should reflect the vehicles that can actually be used.

In CADIS, planners can work with individual vehicles or define the number of vehicles available by vehicle type.

These two approaches support different planning situations.

If specific vehicles are selected, vehicles can be assigned directly to the routes produced by the optimization.

Alternatively, planners can define how many vehicles of each relevant type are available and assign individual vehicles afterwards.

The optimizer can take vehicle characteristics such as payload, pallet positions, dangerous-goods equipment and tail-lift requirements into account.

This is a useful example of why route optimization inside a TMS differs from consumer navigation: the vehicle is part of the planning problem.

Step 3: Decide what the optimization should prioritize

Transport planning usually involves trade-offs.

For example, a planner may want to use as few routes as possible. In another operation, using the available fleet more broadly may be preferable.

The optimization strategy should therefore reflect the operating model rather than relying on one universal definition of an “optimal” route.

An important practical lesson is also to avoid planning theoretical capacity too aggressively when the underlying shipment data contains uncertainty.

If a vehicle is planned to exactly 100% of theoretical capacity, even a small difference between planning data and physical reality can make the plan difficult to execute.

Step 4: Calculate — without immediately changing operations

This is one of the most valuable characteristics of an operational optimization workflow.

The first calculated result should be a scenario, not an irreversible operational decision.

In CADIS, an optimization result can initially be reviewed before it is applied. Planners can run different optimization scenarios and only apply the preferred result afterwards.

That allows the dispatcher to compare outputs such as:

• number of routes,
• total driving time,
• total distance,
• vehicle usage,
• scheduled and unscheduled shipments or collections,
• and route-level statistics.

This turns optimization into a decision-support process rather than a black box.

Step 5: Review the result operationally

A lower total distance does not automatically mean that the plan is better.

Before applying an optimization, review questions such as:

Were all relevant shipments scheduled?

An impressive route KPI is of little value if important orders remain unplanned.

Is vehicle utilization realistic?

Look beyond the number of vehicles and check whether the resulting utilization makes operational sense.

Are there extreme routes?

Average values can hide one route that is exceptionally long or difficult.

Can the resulting plan actually be executed?

The dispatcher should still be able to understand the routes, stops and map output before committing the plan.

CADIS provides route summaries, scheduled and unscheduled orders, route statistics, stop information and map visualization to support this validation.

Step 6: Apply the selected optimization

Only once the planner is satisfied should the calculated scenario become operational.

In CADIS, applying the optimization creates the routes and assigns the relevant shipments and collections to them.

That separation between calculate, review and apply is significant.

It lets optimization support the planner instead of replacing operational judgment.

Route optimization is only part of the planning process

This is where many route optimization projects become too narrow.

Creating efficient routes is valuable. But a transport operation needs much more than efficient geometry.

Before a vehicle leaves the depot, the business may still need to answer:

• Which trip should each shipment belong to?
• Should that assignment happen automatically?
• Which trips repeat every day or every week?
• What happens when new shipments arrive?
• What if the host system already knows the planned trip?
• What if an address cannot be geocoded?
• Can the stop sequence be changed after dispatching?
• How does the optimized trip reach the driver?

This is why route optimization becomes significantly more useful when connected to dispatching, recurring trip planning, loading and execution.

From routing rules to automatic dispatching

Not every shipment needs a global optimization calculation to determine where it belongs.

Many transport networks already contain operational knowledge such as:

• postcode areas,
• outbound routes,
• recurring trips,
• customer-specific rules,
• product requirements,
• or other shipment attributes.

A TMS should be able to use that knowledge.

CADIS supports routing master data and a configurable rules engine for dispatching.

For example, a postcode range can be associated with an outbound route. Dispatch rules can then use shipment characteristics or route information to decide which planned trip should receive the shipment.

Rules can be simulated before they are relied upon operationally.

This creates an important distinction:

Optimization finds efficient solutions. Rules encode operational knowledge.

The strongest transport planning workflows often use both.

Recurring routes do not need to be reinvented every morning

A common misconception about route optimization is that every transport plan should be calculated from scratch.

That rarely reflects how established transport networks operate.

Many trips are recurring:

• Monday to Friday,
• specific weekdays,
• fixed service areas,
• habitual vehicles,
• established routes.

For those operations, trip templates can provide the planning structure while optimization improves the actual workload assigned to the trip.

CADIS supports trip templates for recurring transport. Templates can include route information, operating days and, where appropriate, vehicle information.

This allows planners to combine stable operational structures with dynamic optimization.

Sequence optimization: improving an existing trip

Sometimes the question is not “Which routes should we create?” but simply:

What is the best sequence for the stops already assigned to this trip?

Sequence optimization is particularly useful:

• before loading,
• after manual dispatching,
• when additional collections are added,
• or while refining the daily plan.

In CADIS, first- and last-mile trips can be sequence optimized while taking time restrictions into account. The resulting trip can include updated stop order and planned arrival and departure times.

Planners can also manually adjust a sequence when operational knowledge requires it.

This combination is important. Optimization proposes efficiency; the dispatcher retains control.

What happens when reality changes?

A transport plan begins ageing as soon as operations start.

New collections arrive. Shipment information changes. Stops become problematic. Loading does not always match the original plan.

This is why route optimization should not be evaluated only by the quality of the first morning calculation.

A more useful question is:

How easily can the operation adapt when the plan changes?

For eligible trips, CADIS supports optimizing remaining stops and refining sequences when planning conditions change.

This helps connect optimization with real dispatch operations instead of treating the calculation as a static plan produced once per day.

7 practical mistakes to avoid in TMS route optimization

1. Optimizing bad data

Poor addresses, incorrect shipment dimensions or incomplete vehicle information create poor optimization results.

No routing algorithm can compensate indefinitely for unreliable source data.

2. Treating 100% vehicle capacity as the target

Theoretical utilization and practical loading are not always identical.

Operational buffer can be valuable, especially when shipment data is approximate.

3. Looking only at total kilometres

Distance matters, but it is not the only KPI.

Also examine:

• number of routes,
• driving time,
• vehicle utilization,
• unplanned orders,
• time restrictions,
• and operational feasibility.

4. Optimizing before geocoding is under control

If location quality is poor, route quality will be poor.

Make geocoding quality visible to planners.

5. Replacing dispatching knowledge with an algorithm

Experienced dispatchers know customer requirements, local constraints and recurring operational patterns.

Good software should make that knowledge usable through rules, master data and manual control.

6. Making optimization irreversible

Planners should be able to inspect results and compare scenarios before creating operational trips.

Optimization should support a decision, not force one.

7. Buying a routing tool without considering execution

Ask what happens after the route has been calculated.

A real transport workflow continues through dispatching, loading, communication with drivers, execution, exception handling and monitoring.

That is where the difference between a standalone optimizer and an integrated TMS becomes visible.

A practical checklist for evaluating TMS route optimization software

When comparing solutions, ask whether the system can:

• optimize both deliveries and collections;
• use real vehicle capacities and vehicle characteristics;
• take time restrictions into account;
• identify orders that could not be planned;
• optimize selected subsets as well as broader shipment volumes;
• compare scenarios before applying them;
• show route, stop and map-level results;
• optimize the sequence of an existing trip;
• support geocoding corrections;
• combine routing with configurable dispatch rules;
• use recurring trip templates;
• integrate with the upstream host system;
• and continue the process through operational execution.

The more of these activities take place in disconnected tools, the more manual coordination the dispatcher has to perform.

Where CADIS fits into the route optimization process

CADIS approaches route optimization as part of a wider transportation execution process.

Depending on configuration and use case, the workflow can combine:

Shipment and collection data → routing and dispatch rules → trip creation → route optimization → sequence optimization → loading → driver execution → monitoring.

That integrated approach is particularly relevant for transport operations where planning cannot be separated cleanly from what happens in the depot and on the road.

CADIS route optimization can build routes from shipments and collections while considering the available fleet. Planners can calculate different scenarios, inspect results and apply an optimization only when they are satisfied with it.

For recurring operations, trip templates and routing master data can establish the planning structure.

For automated workflows, dispatch rules can determine how shipments are preassigned to suitable trips.

And when a specific trip needs refinement, sequence optimization can reorder stops while considering planning restrictions.

The objective is not simply to produce an attractive route on a map.

It is to help turn transport demand into an operationally executable trip.

Is route optimization right for every transport operation?

Not every fleet needs the same level of optimization.

If a business runs a handful of fixed routes with almost no daily variation, sophisticated dynamic optimization may provide limited additional value.

Its value tends to increase when:

• shipment volumes change from day to day,
• deliveries and collections must be combined,
• several vehicle types are available,
• capacity constraints matter,
• time restrictions influence planning,
• planners regularly reorganize trips,
• or dispatching requires significant manual effort.

The right question is therefore not simply:

“Do we need route optimization?”

It is:

“Which parts of our current planning process require too much manual decision-making, and which of those decisions can be supported by better data, rules and optimization?”

Final takeaway: optimize the operation, not just the route

Route optimization can reduce unnecessary transport effort, but its biggest impact comes when it is connected to the rest of the TMS workflow.

For transport professionals, the goal should not be to find software that produces the shortest line between a series of stops.

The goal should be to create realistic, efficient and executable transport plans, using the fleet, shipment data and operational rules that exist in the real world.

That means combining automation with dispatcher control, optimization with operational constraints and planning with execution.

That is the role route optimization can play inside CADIS.

Want to see how this would work with your transport operation?

Every network has different shipment structures, fleet constraints and dispatching logic.

Talk to CADIS about your current planning process and see how route optimization, automated dispatching and transport execution could work together in one workflow.

[Request a CADIS demo]

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Fordispatchers, CADIS incorporates a real-time, map-based control center. Userscan view all of the vehicles that are currently in use, along with theirassigned tours and real-time positions, in a matter of seconds.

Dispatchers can easily switch vehicles byclicking, dragging, and dropping the trip to a different vehicle right on themap.

What wasonce a difficult decision-making process is made simpler by this visualworkflow. From driver instructions to warehouse loading, the systemautomatically updates all linked data streams, recalculates ETAs, and verifiesroute optimization parameters.

One of themain components of CADIS's objective to infuse intelligence and adaptabilityinto contemporary logistics management is this real-time vehicle reassignment.

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