Specifiche

The basic idea of CRO is to simulate coral colonies that develop and compete for space on a reef, ultimately forming an optimal structure. Each coral in the reef represents a potential solution to the optimization problem under consideration.

The reef is modeled as a two-dimensional N×M grid. Each grid cell can either be occupied by a coral or left empty. A coral is a coded solution to an optimization problem. For each coral, a fitness (health) function is determined that corresponds to the objective function of the optimization problem.

The ρ₀ ∈ (0,1) parameter determines the initial proportion of the reef occupied by corals, that is, the ratio of occupied cells to the total number of cells at the beginning of the algorithm. Initialization of the reef is performed as follows:

  1. The reef size of N×M and the initial filling fraction ρ₀ are specified.
  2. ⌊ρ₀ × N × M⌋ reef cells are randomly selected to house the starting corals.
  3. Initial corals are generated randomly within the search area and placed in the selected cells.

After the reef is initialized, an iterative process of reef formation and development begins, consisting of several stages:

Broadcast Spawning. For this type of reproduction, a certain proportion of Fₑ existing corals is selected. The selected corals form pairs and create offspring using crossover operators. Each pair produces a larva using the crossover operator (ordinary averaging).

Brooding. The remaining fraction of corals (1-Fₑ) engage in brooding where each coral produces offspring through mutation. For each coral selected for brooding, a larva is created using a mutation operator. The larva typically represents a small random variation of the encoded solution. Larval settlement. After the larvae are formed, each one tries to take its place in the reef during the reproductive stages. The settlement is carried out according to the following rules:

  1. The larva randomly chooses a cell (i, j) in the reef.
  2. If the cell is free, the larva occupies it.
  3. If the cell is occupied, the larva can displace the existing coral only if its fitness is higher: f(larva) > f(Ξᵢⱼ).
  4. If displacement does not occur, the larva may try to settle in another place (up to a maximum k number of attempts).
  5. If after k attempts the larva fails to find a place, it dies.

Asexual reproduction (budding). The best corals in a reef (Fₐ fraction) can reproduce asexually, creating exact copies of themselves (clones). Formally:

  1. Corals are sorted by the fitness function.
  2. The best Fₐ × 100% corals are selected for asexual reproduction.
  3. Each selected coral creates a clone that attempts to settle in the reef according to the same rules as during the larval settlement.

Depredation. At the end of each iteration, the worst corals in the reef may die with Pd probability, making room for new corals in the next iterations.

The reef formation is repeated until the specified stopping criterion is met, such as reaching the maximum number of iterations. After stopping, the best coral in the reef represents the found solution to the optimization problem.


Con risposta

1
Sviluppatore 1
Valutazioni
(16)
Progetti
35
23%
Arbitraggio
4
0% / 50%
In ritardo
2
6%
In elaborazione
2
Sviluppatore 2
Valutazioni
(394)
Progetti
555
41%
Arbitraggio
30
57% / 3%
In ritardo
57
10%
In elaborazione
Pubblicati: 11 codici
3
Sviluppatore 3
Valutazioni
(75)
Progetti
80
6%
Arbitraggio
46
11% / 54%
In ritardo
7
9%
In elaborazione
4
Sviluppatore 4
Valutazioni
(3)
Progetti
4
0%
Arbitraggio
2
0% / 100%
In ritardo
1
25%
Gratuito
5
Sviluppatore 5
Valutazioni
(611)
Progetti
711
33%
Arbitraggio
45
49% / 42%
In ritardo
14
2%
In elaborazione
6
Sviluppatore 6
Valutazioni
(21)
Progetti
27
7%
Arbitraggio
9
33% / 33%
In ritardo
1
4%
In elaborazione
7
Sviluppatore 7
Valutazioni
(1)
Progetti
1
100%
Arbitraggio
0
In ritardo
0
Gratuito
8
Sviluppatore 8
Valutazioni
(1)
Progetti
1
0%
Arbitraggio
1
0% / 100%
In ritardo
0
Gratuito
9
Sviluppatore 9
Valutazioni
(5)
Progetti
6
50%
Arbitraggio
0
In ritardo
1
17%
Gratuito
10
Sviluppatore 10
Valutazioni
(366)
Progetti
444
55%
Arbitraggio
22
55% / 14%
In ritardo
30
7%
Caricato
11
Sviluppatore 11
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
12
Sviluppatore 12
Valutazioni
(13)
Progetti
22
41%
Arbitraggio
8
0% / 50%
In ritardo
3
14%
Gratuito
13
Sviluppatore 13
Valutazioni
(9)
Progetti
11
55%
Arbitraggio
0
In ritardo
0
Gratuito
14
Sviluppatore 14
Valutazioni
(7)
Progetti
5
0%
Arbitraggio
5
0% / 80%
In ritardo
1
20%
In elaborazione
15
Sviluppatore 15
Valutazioni
(12)
Progetti
17
35%
Arbitraggio
5
40% / 20%
In ritardo
1
6%
Caricato
Pubblicati: 6 articoli, 34 codici
16
Sviluppatore 16
Valutazioni
(73)
Progetti
257
53%
Arbitraggio
16
50% / 38%
In ritardo
83
32%
Gratuito
17
Sviluppatore 17
Valutazioni
(7)
Progetti
6
0%
Arbitraggio
4
25% / 75%
In ritardo
2
33%
Gratuito
18
Sviluppatore 18
Valutazioni
(55)
Progetti
92
24%
Arbitraggio
8
75% / 13%
In ritardo
44
48%
Gratuito
19
Sviluppatore 19
Valutazioni
Progetti
1
0%
Arbitraggio
2
0% / 100%
In ritardo
0
Gratuito
20
Sviluppatore 20
Valutazioni
(1)
Progetti
2
0%
Arbitraggio
0
In ritardo
2
100%
Gratuito
21
Sviluppatore 21
Valutazioni
Progetti
2
0%
Arbitraggio
0
In ritardo
1
50%
Gratuito
22
Sviluppatore 22
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
23
Sviluppatore 23
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
24
Sviluppatore 24
Valutazioni
(64)
Progetti
144
46%
Arbitraggio
20
40% / 20%
In ritardo
32
22%
Gratuito
25
Sviluppatore 25
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
26
Sviluppatore 26
Valutazioni
(13)
Progetti
13
38%
Arbitraggio
1
0% / 100%
In ritardo
1
8%
Gratuito
Ordini simili
MT4/MT5 HFT EA us30 30 - 3000 USD
Hello everybody, I'm looking for an experienced MQL4/MQL5 developer to optimize a High-Frequency Trading (HFT) Expert Advisor for both MT4 and MT5. The EA performs consistently and profitably on demo accounts, but when it is run on Raw and Standard live accounts under what appear to be the same trading conditions, it begins generating losses. I do not have the original source code (.mq4/.mq5); I only have the
I have a High-Frequency Trading (HFT) Expert Advisor for both MT4 and MT5 designed primarily for US30 (Dow Jones Index) . The EA performs consistently and profitably on demo accounts, but when I run it on an IC Markets Raw or Standard live account, it starts generating losses under what appear to be the same trading conditions. At this time, I cannot provide the source code (.mq4/.mq5). I can only provide the
Standby Description . Prop Firm Environment . ( Monitor Execution and Handling Environment Changes as Required ) . Technical Issues . Delete extra lines of code (Clean Code , Folder) . Asset related translation , no need for Logic Alteration
Only Technical Issues . Familiarization to Different Symbols . [Again Technical Assistance Only] . Deleting extra lines of code , Not Required Folders (Clean Code) . No Need for Logic Alteration (Strictly)
EA Crafter 500+ USD
Act as a professional Quantitative Developer and Risk Manager. I want to build a systematic trading strategy rulebook that prioritizes capital preservation and statistical edge over raw performance. Please generate a structured trading strategy using the following framework: 1. ASSET CLASS & TIMEFRAME: - Asset: [e.g., Apple (AAPL), Bitcoin (BTC), or EUR/USD] - Timeframe: [e.g., 5-minute, 1-hour, Daily] 2. CORE

Informazioni sul progetto

Budget
850+ USD
Scadenze
da 3 a 8 giorno(i)