Mealpy

+ Add transfer function module (please read [this paper](https://www.sciencedirect.com/science/article/abs/pii/S2210650212000648) )
+ Add two new datatypes: `TransferBinaryVar` and `TransferBoolVar`.
+ Fix bug un-order variables in `PermutationVar` data type.
+ Update data type of encoded solution in `BoolVar` data type.
+ Update correct function in `BoolVar` and `BinaryVar`.
+ Fix bug reproduce results in `GA`, `WCA`, and `EHO` optimizers.
+ Fix bug higher probability of 0 value in `IntegerVar` data type.

**Based on our new proposed classes, solving continuous and discrete problems is never that easy.**

Add
+ `space` module with: FloatVar, IntegerVar, StringVar, BoolVar, PermutationVar, BinaryVar, and MixedSetVar classes
* **FloatVar**: handle problem with solution's format as float value
* **IntegerVar**: handle problem with solution's format as integer value
* **StringVar**: handle problem with solution's format as string value
* **BoolVar**: handle problem with solution's format as boolean value (True or False)
* **PermutationVar**: handle problem with solution's format as permutation value
* **BinaryVar**: handle problem with solution's format as binary value (0 or 1)
* **MixedSetVar**: handle problem with solution's format as mixed discrete set
+ `target` module with **Target** class contains:
* `objectives` (list), `weights` (list) to calculate fitness, and `fitness` (number)
+ `agent` module with: **Agent**te class that is a placeholder for a search agent, it contains at least two attributes:
* `solution` (position - np.ndarray), and a `target` object

Update
+ Convert all optimizers to use new classes
+ Convert Tuner and MultiTask classes
+ Rename all un-official (developed by our team) optimizers to `DevOptimizerName`
+ Update tests and documents
+ Update some examples, not all examples have converted yet (utils and applications folders)

Update
+ Remove deepcopy() to improve the computational speed
+ Update the parameter's order in Tuner class
+ Update the saving's bug when using Termination in Multitask
+ Remove ILA optimizer
+ Rename "amend_position()" definition in some algorithms to "bounded_position()".
+ Add a "amend_position()" function in Optimizer class. This function will call two functions.
+ bounded_position() from optimizer. This means for optimizer level (get in valid range of position)
+ amend_position() from problem. This means for problem level (transform to the correct solution)
+ Fix bugs coefficients in GWO-based optimizers.
+ Fig bug cls.epoch in SCSO optimizer.
+ Fix bug cls.dyn_pop_size when pop_size is small value
+ Move SHADE-based optimizers from DE to SHADE module in evolutionary_based group
+ Add Improved Grey Wolf Optimization (IGWO) in GWO algorithm
+ Add Tabu Search (TS) to math-based group
+ Add get_all_optimizers() and get_optimizer_by_name() in Mealpy
+ Rename the OriginalSA to SwarmSA in SA optimizer
+ Add the OriginalSA and GaussianSA in SA optimizer
+ Update parameters in OriginalHC and SwarmHC
+ Update ParameterGrid class to produce the dict with same order as original input
+ Add export_figures() to Tuner class. It can draw the hyperparameter tuning process.
+ Fix several bugs in docs folders.

Update
+ Fix bug in roulette-wheel-selection in Optimizer
+ Update multitask with input modes and terminations
+ Update Tuner with more input parameters
+ Add Lévy flight, and the selective opposition version of the artificial rabbit algorithm (LARO)
+ Add Modified Gorilla Troops Optimization (MGTO)
+ Update Giant Trevally Optimizer as requested by the authors
+ Matlab101GTO: This version was used to produce the results presented in the paper.
+ Matlab102GTO: This is a new version provided by the authors (Matlab link), which has been updated recently to
reduce computation time.
+ OriginalGTO: This version is implemented exactly as described in the paper.

Update

+ Fixed bug all fitness values are equals in function "get index roulette wheel selection" in Optimizer class
+ Rename AdaptiveAEO by AugmentedAEO (Add reference)
+ Update text of Dwarf Mongoose Optimization Algorithm belongs to Swarm-based group
+ Fixed all tests and update all documents
+ Update Termination class, you can now design multiple Stopping Conditions for Optimizer

+ Bio-based group:
+ Add Brown-Bear Optimization Algorithm (BBOA)
+ Ref: A Novel Brown-bear Optimization Algorithm for Solving Economic Dispatch Problem

+ Human-based group:
+ Add Heap-based optimizer (HBO)
+ Ref: Heap-based optimizer inspired by corporate rank hierarchy for global optimization
+ Add War Strategy Optimization (WarSO)
+ Ref: War Strategy Optimization Algorithm: A New Effective Metaheuristic Algorithm for Global Optimization
+ Add Human Conception Optimizer (HCO)
+ Ref: A novel Human Conception Optimizer for solving optimization problems

+ Math-based group:
+ Add Q-Learning Embedded Sine Cosine Algorithm (QLESCA)
+ Ref: Q-learning embedded sine cosine algorithm (QLESCA)
+ Add Success History Intelligent Optimizer (SHIO)
+ Ref: Success history intelligent optimizer

+ Physics-based group:
+ Add rime-ice (RIME)
+ Ref: RIME: A physics-based optimization
+ Add Energy Valley Optimizer (EVO)
+ Ref: Energy valley optimizer: a novel metaheuristic algorithm
+ Add Chernobyl Disaster Optimizer (CDO)
+ Ref: Chernobyl disaster optimizer (CDO): a novel meta-heuristic method for global optimization
+ Add Fick's Law Algorithm (FLA)
+ Ref: Not accepted yet

+ Evolutionary-based group:
+ Add CMA-ES and Simple-CMA-ES
+ Ref: Completely derandomized cls-adaptation in evolution strategies.

+ Swarm-based group:
+ Add Wavelet Mutation and Quadratic Interpolation MRFO (WMQIMRFO)
+ Ref: An enhanced manta ray foraging optimization algorithm for shape optimization of complex CCG-Ball curves
+ Add Egret Swarm Optimization Algorithm (ESOA)
+ Ref: Egret Swarm Optimization Algorithm: An Evolutionary Computation Approach for Model Free Optimization
+ Add Sea-Horse Optimization (SeaHO)
+ Ref: Sea-horse optimizer: A nature-inspired meta-heuristic for global optimization and engineering application
+ Add Mountain Gazelle Optimizer (MGO)
+ Ref: Mountain Gazelle Optimizer: A new Nature-inspired Metaheuristic Algorithm for Global Optimization Problems
+ Add Golden jackal optimization (GJO)
+ Ref: Golden jackal optimization: A novel nature-inspired optimizer for engineering applications
+ Add Fox Optimizer (FOX)
+ Ref: FOX: a FOX-inspired optimization algorithm
+ Add Giant Trevally Optimizer (GTO)
+ Ref: Giant Trevally Optimizer (GTO): A Novel Metaheuristic Algorithm for Global Optimization and Challenging Engineering Problems

+ **Warning**: Please check the original paper before you want to use these algorithms.
+ Add Zebra Optimization Algorithm (ZOA)
+ Ref: Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm
+ Add Osprey Optimization Algorithm (OOA)
+ Ref: Osprey optimization algorithm: A new bio-inspired metaheuristic algorithm for solving engineering optimization problems
+ Add Coati Optimization Algorithm (CoatiOA)
+ Ref: Coati Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
+ Add Pelican Optimization Algorithm (POA)
+ Ref: Pelican optimization algorithm: A novel nature-inspired algorithm for engineering applications
+ Add Northern Goshawk Optimization (NGO)
+ Ref: Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems
+ Add Serval Optimization Algorithm (ServalOA)
+ Ref: Serval Optimization Algorithm: A New Bio-Inspired Approach for Solving Optimization Problems
+ Add Siberian Tiger Optimization (STO)
+ Ref: Siberian Tiger Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Engineering Optimization Problems
+ Add Walrus Optimization Algorithm (WaOA)
+ Ref: Walrus Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm
+ Add Tasmanian Devil Optimization (TDO)
+ Ref: Tasmanian devil optimization: a new bio-inspired optimization algorithm for solving optimization algorithm
+ Add Fennec Fox Optimization (FFO)
+ Ref: Fennec Fox Optimization: A New Nature-Inspired Optimization Algorithm
+ Add Teamwork Optimization Algorithm (TOA)
+ Ref: Teamwork Optimization Algorithm: A New Optimization Approach for Function Minimization/Maximization




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Update

+ Add validator when variable can be both int/float value
+ Add algorithms to evolutionary-based group:
+ EliteSingleGA and EliteMultiGA class
+ Add algorithms to math-based group:
+ weIghted meaN oF vectOrs (INFO) algorithm
+ RUNge Kutta optimizer (RUN)
+ Circle Search Algorithm (CSA)
+ Add algorithms to bio-based group:
+ Barnacles Mating Optimizer (BMO)
+ Symbiotic Organisms Search (SOS)
+ Seagull Optimization Algorithm (SOA)
+ Tunicate Swarm Optimization (TSA)
+ Add algorithms to swarm-based group:
+ Hybrid Grey Wolf - Whale Optimization Algorithm (GWO_WOA)
+ Marine Predators Algorithm (MPO)
+ Honey Badger Algorithm (HBA)
+ Sand Cat Swarm Optimization (SCSO)
+ Tuna Swarm Optimization (TSO)
+ African Vultures Optimization Algorithm (AVOA)
+ Artificial Rabbits Optimization (ARO)
+ Artificial Gorilla Troops Optimization (AGTO)
+ Dwarf Mongoose Optimization Algorithm (DMOA) (weak algorithm)

+ Add algorithms to human-based group:
+ Student Psychology Based Optimization (SPBO) (weak algorithm)

+ Fix problem with 1 dimension
+ Enhanced the get index roulette wheel selection in Optimizer class

+ Update check parallel mode in Optimizer
+ Update algorithms that don't support parallel modes
+ Update the shebang ! with python codes
+ Update examples

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