GH2_V0
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WHAT IS IT?
This model demonstrates diffusion of a quantity through a directed network. The quantity moves among nodes in the network only along established, directed links between two nodes.
The simple rules that drive this diffusion lead to interesting patterns related to the topology, density, and stability of the network. Furthermore, the model may be useful in understanding the basic properties of dynamic processes on networks, and provides a useful starting point for designing more complex and realistic network-based models.
HOW IT WORKS
In each tick, each node shares some percentage (defined by the DIFFUSION-RATE slider) of its "value" quantity with its neighbors in the network. Specifically, the amount of shared value is divided equally and sent along each of the outgoing links from each node to each other node. If a node has no outgoing links, then it doesn't share any of it's value; it just accumulates any that its neighbors have provided via incoming links.
Note that because it is a directed network, node B may give value to node A even if node A doesn't give back.
The size of each node shows how much "value" that node has, where the area of the node is proportional to its value. The brightness of a link represents how much value just flowed through that edge.
HOW TO USE IT
Choose the size of network that you want to model using the GRID-SIZE slider. Choose the expected density of links in the network using the LINK-CHANCE slider.
To create the network with these properties, press SETUP.
The DIFFUSION-RATE slider controls how much "value" each node shares with its neighbors during a given time step.
Press the GO button to run the model.
The REWIRE-A-LINK button causes one link to disappear, and a new one to appear elsewhere in the grid.
The KEEP-REWIRING button causes a continual rewiring of links to occur.
The histogram displays the number of nodes whose values fall into certain ranges. For instance, you might see that there are many nodes with nearly zero value, while there are just a few nodes with very large value.
THINGS TO NOTICE
As time passes, the network tends toward an equilibrium state. (Is that always the case, or is it possible for a network to never settle down?)
However, if you run both the GO and KEEP-REWIRING buttons at the same time, then the network will never completely settle down. If you ran the model in this way for a long long time, would the distribution of value across the nodes in the network be uniform, if you averaged across time? Or would nodes near the edges of the grid tend to have more or less value?
THINGS TO TRY
Try running the model with a small 3x3 grid. How many nodes end up with positive value (not approaching zero) after running the model for a while? Sometimes just a single node ends up with all of the value, while other times every node in the network can sustain a positive value. What properties of the network are necessary in order for every node to sustain a positive value? Are these properties more or less likely to occur with large networks?
EXTENDING THE MODEL
Imagine you are modeling a business economy, where each node is a business, and it has suppliers and customers (represented by directed links from that node). Is it reasonable to assume that as a business accumulates more profit from sales, it will in turn purchase more from its suppliers? In order to more accurately match this economic model, change the model into a supply chain model where each node also has an inventory level, and a price they are charging per unit. Try to come up with reasonable rules for how many units each business decides to buy or sell.
How would you change this model to more accurately represent water flowing (or being pumped) through pipes? Should the links be directed or undirected? What if water is continually flowing in or out of the system at certain locations?
NETLOGO FEATURES
This model works in a manner analogous to NetLogo's diffuse
command, which causes patches to all share with their neighbors portions of the value of some variable.
However, whereas the neighbor relationship in patches is symmetric, this model uses directed links, which can be used to create asymmetric relationships between agents. If you used undirected links, the behavior of this model would more closely resemble the diffuse
command, where the value of all the nodes would eventually become the same.
In this model, there are two link-breeds: one for active links (which are shown in the view) and another for inactive links (which are invisible). This makes "rewiring" of links easier, because rather than killing a link and creating a new link, we can just change the breed of a link and hide or show it.
Though it is not used in this model, there exists a network extension for NetLogo that you can download at: https://github.com/NetLogo/NW-Extension.
RELATED MODELS
Virus on a Network
HOW TO CITE
If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.
For the model itself:
- Stonedahl, F. and Wilensky, U. (2008). NetLogo Diffusion on a Directed Network model. http://ccl.northwestern.edu/netlogo/models/DiffusiononaDirectedNetwork. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
Please cite the NetLogo software as:
- Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
COPYRIGHT AND LICENSE
Copyright 2008 Uri Wilensky.
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.
Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu.
Comments and Questions
directed-link-breed [supplier-links supplier-link] directed-link-breed [client-links client-link] breed [farmers farmer] breed [F_T First_transportation] breed [FPP First_production_plant] breed [S_T Second_transportation] breed [SPP Second_production_plant] turtles-own [ prod_capacity prod_level sustainability_attitude innovativeness capital revenue cost profit demand prod_offer price my_score max-score max-score-turtle ordered-clients ordered-suppliers ordered-transport target-FPP target-farmers portfolio demander supplier p my_self my-sup my-co2-prod ] Farmers-own [ ] FPP-own[ sugare_cane_prod bioethanol_prod ] SPP-own[ ] F_T-own [ ] links-own [ flow n_flow active] globals [ yellow-linked-agents avg-sustainability avg-innovativeness total-spp-production simulation-running CO2_Emissions ] ;;;;;;;;;;;;;;;;;;;;;;;; ;;; Setup Procedures ;;; ;;;;;;;;;;;;;;;;;;;;;;;; to setup clear-all set CO2_Emissions 0 set simulation-running true set total-spp-production 0 ; create the agents create-farmers N_Farmers create-F_T N_First_transp. create-FPP N_First_Prod_Plant create-S_T N_Second_transp. create-SPP N_Second_Prod_Plant visual ask turtles[ set portfolio [0 0 0] ] capacity set avg-sustainability 0 set avg-innovativeness 0 reset-ticks end to go ask turtles [ create-list-of-suppliers create-list-of-clients if breed = farmers [farmer_production] valuate_demand_and_offer build_a_supply_chain ;if breed = FPP [highlight-complete-supply-chain] ] ask links with [active = false] [die] calculate_av_score if not simulation-running [ stop ] ; Reset production level every 12 ticks and gradually increase it to reach near production capacity ifelse (ticks mod 12 = 0) [ CO2_Emission_Count reset_production R&Dinvestment ] [colors] eq_stop display tick end to build_a_supply_chain if demand > 0 [choose_a_partner] end to CO2_Emission_Count ask turtles [ if breed = farmers [ set my-co2-prod my-co2-prod + (prod_level * CO2-Emission-For-Sugarcane-production) set CO2_Emissions CO2_Emissions + my-co2-prod] if breed = FPP [ set my-co2-prod my-co2-prod + (item 0 portfolio * CO2-Emission-For-Bioethanol-production) set CO2_Emissions CO2_Emissions + my-co2-prod] ] end to create-list-of-suppliers if breed = FPP [ ; Valuta Farmers come fornitori let potential-suppliers farmers with [prod_offer > 0] set ordered-suppliers sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w + [prod_offer] of w) > ([my_score] of q - distance q - [item 0 price] of q + [prod_offer] of q)] potential-suppliers if length ordered-suppliers > radius [ set ordered-suppliers sublist ordered-suppliers 0 radius] ] if breed = SPP [ let potential-suppliers FPP with [prod_offer > 0] set ordered-suppliers sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w + [prod_offer] of w) > ([my_score] of q - distance q - [item 0 price] of q + [prod_offer] of q)] potential-suppliers if length ordered-suppliers > radius [ set ordered-suppliers sublist ordered-suppliers 0 radius] let potential-transport F_T set ordered-transport sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w) > ([my_score] of q - distance q - [item 0 price] of q)] potential-transport ] end to create-list-of-clients if breed = farmers [ let potential-clients FPP with [demand > 0] set ordered-clients sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w) > ([my_score] of q - distance q - [item 0 price] of q)] potential-clients if length ordered-clients > radius [set ordered-clients sublist ordered-clients 0 radius] ] if breed = FPP[ let potential-clients SPP with [demand > 0] set ordered-clients sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w) > ([my_score] of q - distance q - [item 0 price] of q)] potential-clients if length ordered-clients > radius [set ordered-clients sublist ordered-clients 0 radius] ; Valuta F_T come channels let potential-transport F_T with [prod_offer < [demand] of myself] set ordered-transport sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w) > ([my_score] of q - distance q - [item 0 price] of q)] potential-transport ] if breed = F_T [ let potential-clients FPP with [demand > 0] ; FT che hanno bisogno di più produzione set ordered-clients sort-by [[w q] -> ([my_score] of w - distance w - [item 0 price] of w) > ([my_score] of q - distance q - [item 0 price] of q)] potential-clients if length ordered-clients > radius [set ordered-clients sublist ordered-clients 0 radius] ] end to reset_production set total-spp-production precision (total-spp-production + sum ([prod_level] of SPP)) 0 ask turtles[ set prod_offer prod_offer + prod_level set prod_level 0.1 ] end to valuate_demand_and_offer if breed = FPP[ let dem prod_capacity - prod_level set demand dem * 18.0505 ] if breed = SPP [ let dem prod_capacity - prod_level set demand dem * 23.0833] if (demand > 0) [set demander true] if (prod_offer > 0) [set supplier true] end to farmer_production let increment min(list ((prod_capacity - prod_level) / (12 - (ticks mod 12))) prod_capacity) set prod_level precision (prod_level + increment) 2 set prod_offer prod_level set portfolio replace-item 0 portfolio prod_level end to calculate_av_score if any? links with [color = yellow] [ set yellow-linked-agents (turtle-set [end1] of links with [color = yellow] [end2] of links with [color = yellow]) set avg-sustainability mean [sustainability_attitude] of yellow-linked-agents set avg-innovativeness mean [innovativeness] of yellow-linked-agents] end to R&Dinvestment ask turtles with [(breed = FPP or breed = SPP or breed = farmers) and my-sup = 0][ ifelse (capital > R&D_cost) and (ticks != 0)[ ; Calculate the difference between the agent's and the averages let diff-sustainability abs(sustainability_attitude - avg-sustainability) let diff-innovativeness abs(innovativeness - avg-innovativeness) ; Deduct the R&D cost set capital capital - R&D_cost ; Decide in which field to invest based on the greater difference ifelse diff-sustainability > diff-innovativeness [ ; Invest in sustainability set sustainability_attitude sustainability_attitude + (diff-sustainability) ; Adjust the multiplier as needed ] [; Otherwise Invest in innovation set innovativeness innovativeness + (diff-innovativeness ) ; Adjust the multiplier as needed ] set prod_capacity prod_capacity + 10000 set my_score innovativeness + sustainability_attitude set color pink ][]] end to capacity ask turtles[ set prod_level 0.1 set sustainability_attitude random 100 + 1 set innovativeness random 100 + 1 set my_score innovativeness + sustainability_attitude if breed = farmers [set prod_capacity random (9E+06 - 5E+06 + 1) + 5E+06 set capital random 1E+10 ] if breed = FPP [set prod_capacity random (2.22E+08 - 1E+08 + 1) + 1E+08 set capital random 1E+10 ] if breed = SPP [set prod_capacity random (1E+07 - 5E+06 + 1) + 5E+06 set capital random 1E+010 ] ] ask n-of %Big_farmers farmers [ set size 1.1 set prod_capacity random (8.58E+08 - 9E+06 + 1) + 9E+06 set capital random (1E+09 - 1E+06 + 1) + 1E+06 ] end to production [ff] if breed = FPP [ let r1 item 0 portfolio let r2 item 1 portfolio let r3 item 2 portfolio ; Crea la lista portfolio con i valori calcolati set portfolio replace-item 0 portfolio (r1 + 0.0554 * ff) set portfolio replace-item 1 portfolio (r2 + 0.0514 * ff) set portfolio replace-item 2 portfolio (r3 + 0.113 * ff) ] if breed = SPP [ if co-product_scenario = "acetaldehyde" [ let r1 item 0 portfolio let r2 item 1 portfolio ; Crea la lista portfolio con i valori calcolati set portfolio replace-item 0 portfolio (r1 + 0.0438 * ff) set portfolio replace-item 1 portfolio (r2 + 0.9562 * ff)] if co-product_scenario = "acetic acid" [ let c1 item 0 portfolio let c2 item 1 portfolio ; Crea la lista portfolio con i valori calcolati set portfolio replace-item 0 portfolio (c1 + 0.0875 * ff) set portfolio replace-item 1 portfolio (c2 + 1.3036 * ff)] if co-product_scenario = "acetal" [ let w1 item 0 portfolio let w2 item 1 portfolio let w3 item 2 portfolio ; Crea la lista portfolio con i valori calcolati set portfolio replace-item 0 portfolio (w1 + 0.0146 * ff) set portfolio replace-item 1 portfolio (w2 + 0.8551 * ff) set portfolio replace-item 2 portfolio (w3 + 0.1303 * ff)] ] end to choose_a_partner ; for agents with demand > 0 let u random 100 let z random 100 ifelse u > z [ if breed = FPP or (breed = SPP) [ let dem demand ; Cerca tra i fornitori (Farmers) foreach ordered-suppliers [supp -> if (dem > 0) and ([prod_offer] of supp > 0.1) and (capital > (dem * [item 0 price] of supp)) and (member? self [ordered-clients] of supp) [ let tt min list dem [prod_offer] of supp if breed = FPP [ create-supplier-link-from supp ; Creazione del link di fornitura [ set n_flow n_flow + 1 set active true activate_link] set dem dem - tt ] if breed = SPP [ create-supplier-link-from supp ; Creazione del link di fornitura [ set n_flow n_flow + 1 set active true activate_link] set dem dem - tt ] ]]]][stop] end to find_transport [flow_material supplie clien] ; Identifica un F_T adatto per il trasporto if breed = FPP [ let available-FTs F_T with [capital >= (flow_material * item 0 price)] ; Semplice filtro di esempio if any? available-FTs [ let selected-FT one-of available-FTs ; Supponiamo che il FPP conosca già i suoi farmer collegati ask selected-FT [ set color white move-ft-gradually supplie ; Sostituisci move-to con move-ft-gradually move-ft-gradually clien ; Ripeti per il movimento verso il FPP ]]] if breed = SPP[ let available-STs S_T with [capital >= (flow_material * item 0 price)] ; Semplice filtro di esempio if any? available-STs [ let selected-ST one-of available-STs ; Supponiamo che il FPP conosca già i suoi farmer collegati ask selected-ST [ set color white move-ft-gradually supplie ; Sostituisci move-to con move-ft-gradually move-ft-gradually clien ; Ripeti per il movimento verso il FPP ]]] end to activate_link set flow min (list [prod_offer] of end1 [demand] of end2) set label precision (flow) 1 let z end1 let y end2 ask end1[ set my-sup my-sup + 1 let rev (item 0 price * [flow] of myself) set prod_offer prod_offer - [flow] of myself let j (item 0 portfolio) * (item 0 price) let k (item 1 portfolio) * (item 1 price) let l (item 2 portfolio) * (item 2 price) set capital capital + rev ; Aumenta la sostenibilità e l'innovazione ricevendo conoscenza ;set sustainability_attitude sustainability_attitude + (0.05 * [flow] of myself) ;set innovativeness innovativeness + (0.05 * [flow] of myself) ] ask end2[ set my-sup my-sup + 1 if breed = FPP [set prod_level precision (prod_level + (0.0554 * [flow] of myself))2 set capital capital - ([item 0 price] of z * [flow] of myself) ] ;per gli SPP il mercato non è simulato per cui il capital viene aggiornato qui hp che tutto l'idrogeno verde prodotto trovi mercato if breed = SPP and co-product_scenario = "acetaldehyde" [set prod_level precision (prod_level + (0.0433 * [flow] of myself))2 set capital capital - ([item 0 price] of z * [flow] of myself) ] if breed = SPP and co-product_scenario = "acetic acid" [set prod_level precision (prod_level + (0.0875 * [flow] of myself))2 set capital capital - ([item 0 price] of z * [flow] of myself) ] if breed = SPP and co-product_scenario = "acetal" [set prod_level precision (prod_level + (0.0146 * [flow] of myself))2 set capital capital - ([item 0 price] of z * [flow] of myself) ] market z y let ff [flow] of myself production ff ; Aumenta la sostenibilità e l'innovazione ricevendo conoscenza set sustainability_attitude sustainability_attitude + (0.05 * [flow] of myself) set innovativeness innovativeness + (0.05 * [flow] of myself) find_transport [flow] of myself y z ] set flow 0 set active false end to market [sup cli] if breed = SPP[ if co-product_scenario = "acetaldehyde"[ set capital capital + (([item 0 price] of self * (0.0433 * [flow] of myself)) + ([item 1 price] of self * (0.9567 * [flow] of myself))) ] if co-product_scenario = "acetic acid"[ set capital capital + (([item 0 price] of self * (0.0875 * [flow] of myself)) + ([item 1 price] of self * (1.3036 * [flow] of myself)))] if co-product_scenario = "acetal" [ set capital capital + (([item 0 price] of self * (0.0146 * [flow] of myself)) + ([item 1 price] of self * (0.8551 * [flow] of myself))) ]] if breed = FPP [ set capital capital + (([item 1 price] of self * (0.0514 * [flow] of myself)) + ([item 2 price] of self * ( 0.113 * [flow] of myself)))] end to eq_stop if total-spp-production >= Gh2_demand [ let f ticks / 12 print (word "SPP production has met the GH2 demand of " Gh2_demand " Kg in " f "years") set simulation-running false ; Use this to signal the simulation to stop ] end to visual ask patches [ if (pxcor = 0 and pycor < 0) or (pycor = 0 and pxcor > 0) [ set pcolor sky ; Usiamo il colore "sky" per l'azzurro ] ] set-default-shape links "small-arrow-link" ask turtles [ set size 0.8 set price [0 0 0] set demander false set supplier false if breed = farmers [ set ordered-clients [] set shape "flower" set color green let price_sugarcane random-float one-of (range 0.022 0.026 0.001) set price replace-item 0 price price_sugarcane setup-random-position] if breed = FPP [ set ordered-clients [] set ordered-suppliers [] set shape "first prod" set color red let price_bioethanol random-float one-of (range 0.8 0.9 0.001) let price_sugar random-float one-of (range 0.3 0.4 0.001) let price_bioeletr random-float one-of (range 0.07 0.085 0.001) set price replace-item 0 price price_bioethanol set price replace-item 1 price price_sugar set price replace-item 2 price price_bioeletr setup-random-position ] if breed = SPP [ set ordered-suppliers [] set shape "second prod" set color 116 let price_h2 random-float one-of (range 4 5 0.01) set price replace-item 0 price price_h2 if co-product_scenario = "acetaldehyde" [let price_coproduct random-float one-of (range 3 10 1) set price replace-item 1 price price_coproduct ] if co-product_scenario = "acetic acid" [ let price_coproduct random-float one-of (range 0.8 0.9 0.001) set price replace-item 1 price price_coproduct] if co-product_scenario = "acetal"[ let price_coproduct random-float one-of (range 0.8 1.25 0.01) set price replace-item 1 price price_coproduct ] let a one-of (range 13 15 1) let c one-of (range -15 -13 1) set xcor a set ycor c ] if breed = F_T [ set shape "truck" set color yellow setup-random-position] if breed = S_T[ set shape "bot" set color white ifelse random-float 1.0 < 0.5 [ ; Posizione lungo l'asse y (pxcor = 0, pycor < 0) setxy 0 (random -15) ] [ ; Posizione lungo l'asse x (pycor = 0, pxcor > 0) setxy random 15 0 ] ]] end ; Funzione per impostare la posizione in uno dei quadranti 1, 3, 4 to setup-random-position ; Continua a scegliere una posizione finché non ne trova una valida let x random-xcor let y random-ycor ; Controlla se la posizione è valida (non nel quadrante 2) if not (x > 0 and y < 0) [ setxy x y ] end to move-ft-gradually [target] let steps 3 ; Numero di passi per raggiungere la destinazione let dx_1 (([xcor] of target - xcor) / steps) let dy_1 (([ycor] of target - ycor) / steps) repeat steps [ set xcor xcor + dx_1 set ycor ycor + dy_1 display ; Aggiorna l'interfaccia grafica ad ogni passo ; Puoi inserire un wait qui se vuoi rallentare visivamente il movimento, es: wait 0.05 ] end to colors ask turtles[ if breed = farmers [ set color green] if breed = FPP [ set color red] if breed = SPP [ set color violet]] end ;to highlight-complete-supply-chain ; ; ; Iterate over FPP agents ; ; ; Check if there are incoming links from Farmers ; let has-farmer-link? any? in-link-neighbors with [breed = farmers] ; ; Check if there are outgoing links to SPPs ; let has-SPP-link? any? out-link-neighbors with [breed = SPP] ; ; ; If both conditions are met, highlight all related links in yellow ; if has-farmer-link? and has-SPP-link? [ ; ; Highlight incoming links from Farmers ; ask my-in-links with [[breed] of end1 = farmers] [ ; set color yellow ; ] ; ; Highlight outgoing links to SPPs ; ask my-out-links with [[breed] of end2 = SPP] [ ; set color yellow ; ] ; ] ; ;end
There is only one version of this model, created 4 months ago by Simonetta Primario.
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