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Evolver 7.5
遺傳演繹應用系統
The Innovative Optimizer for Windows Genetic algorithm
軟體代號:821
瀏覽次數:11189
Windows2000WindowsXP
安裝序號
產品介紹!

可在Excel試算表內做用遺傳演譯Genetic algorithm (GA)的方法對複雜的細系統做最佳化),

可以分析財務,分配,排程,預算等等

Find the Best Solutions to any Optimization Problem

Wouldn’t you like to know the best allocation of your limited resources to maximize your profits?  Or the most efficient schedule to minimize costs?  Or the most efficient remediation strategy to minimize environmental damage?

With Evolver, you can tackle tough problems like these, and much more. Evolver is an advanced, yet simple-to-use optimization add-in for Microsoft Excel. Evolver uses innovative genetic algorithm (GA), OptQuest, and linear programming technology to quickly solve problems in finance, distribution, scheduling, resource allocation, manufacturing, budgeting, engineering, and more. Virtually any type of problem that can be modeled in Excel can be solved by Evolver, including otherwise unsolvable, complex nonlinear problems. Evolver has a unique ability arrive at the best overall “global” solution to a problem—solutions traditional solvers typically miss.

Learn how to get started quickly in Evolver 
Watch videos of Evolver features

Evolver has also been fully translated into SpanishPortugueseGermanFrenchRussianJapanese, andChinese.

New in Version 7 – Efficient Frontier Analysis

Efficient frontier analysis is very common in financial modeling, particularly in the area of portfolio optimization. An efficient frontier is a graph mapping out the optimal return for any risk level one is willing to accept.

For each acceptable risk level you specify, Evolver performs an optimization. In a financial portfolio, we are optimizing the expected return by changing the various allocations of investment funds. The risk level is a constraint that we vary across a range of possible values. The resulting efficient frontier is a 2-dimensional graphical representation of many optimization results. With efficient frontiers, you can greatly enhance the performance of any portfolio.

The efficient frontier feature is also applicable outside the field of portfolio optimization: it can be used whenever you want to perform many optimizations fast in order to analyze tradeoffs between two quantities in an optimization problem.

 

 

Calculation of the efficient frontier in RISKOptimizer.

 

Evolver Industries and Applications

Evolver is used to solve optimization problems in a wide range of industries, from finance to airlines to manufacturing.

INDUSTRYSAMPLE APPLICATION
 
AIRLINES and HOTELS Yield management with uncertain demand
MANUFACTURING
» Case Studies
Job shop, production, manpower scheduling
Inventory management 
Capacity planning
Product mix decisions
FINANCE Portfolio maximization
Hedging strategies 
Portfolio balancing 
Retirement planning
ENERGY UTILITIES
» Case Studies
EPA emissions standards
GENERAL Market entry timing
Bidding decisions 
RETAIL Optimization of ordering policies

How Evolver Works

Standard optimization programs such as Excel’s Solver are good at finding the best “local” solution, or combination of values to maximize or minimize the outcome of a straightforward spreadsheet model given certain constraints. They find a solution which seems to be producing favorable results and continue to work on that basis, without trying new solutions. This is known as “hill climbing.” However, these programs are not set up to handle more complicated, nonlinear problems where the best local solution may not be the best absolute answer. Evolver, using innovative “mutations” and combinations of solutions, or “organisms,” is well-suited to finding the best overall answer by exploring the entire universe of possible answers.

Using Evolver involves three simple steps:

1. Set Up Your Model. 
The Evolver Model window provides one-stop setup for all optimization problems. Here you specify the target cell, identify cells to adjust, and define constraints. Adjustable cells and constraints support cell ranges for easy setup and changes, while target cells can be maximized, minimized, or approach a specific goal.

 See the Evolver Model window

Defining Ranges and Stopping Conditions 
When defining adjustable cells, you can specify the maximum and minimum boundaries of ranges of cells directly in Excel, greatly simplifying setup and making changes easy. For example, you can tell Evolver to adjust cells B1:B5, with a minimum value for each in A1:A5, and a maximum value for each in C1:C5. Multiple groups of cells may be specified, with multiple ranges in each group.

You must also define constraints in your model. For example, there may be limited resources which must be modeled. When defining constraints (hard or soft), you can also specify minimums and maximums with cell ranges.

Finally, set stopping conditions for your optimization, telling Evolver when to stop the optimization.

Solving Methods
Evolver uses six different solving methods that you can specify to find the optimal combination of adjustable cells. Different methods are used to solve different types of problems. The six methods are:

  • Recipe - a set of variables which can change independently.
  • Grouping - a collection of elements to be placed into groups.
  • Order - an ordered list of elements.
  • Budget - recipe algorithm, but total is kept constant.
  • Project - order algorithm, but some elements precede others.
  • Schedule - group algorithm, but assign elements to blocks of time while meeting constraints.

Evolver also allows a great degree of control over how it performs the optimization itself. You can set optimization parameters, runtime settings, control macros and more in the Evolver Settings dialog.

2. Run the Optimization. 
Click the Start icon to start the optimization. Evolver will start generating trial solutions in an effort to achieve the target set in Step 1. The summary Evolver Progress window appears, showing optimization status and best answer achieved thus far. This window lets you pause, stop, and run the optimization using playback controls. You can also monitor progress in detail with the Evolver Watcher. Tabbed reports show real-time updates on best answers achieved, all solutions tried, the diversity of solutions being tried, and more.

 See the Evolver Watcher

What Optimization Does 
During an optimization, Evolver generates a number of trial solutions and uses genetic algorithms, OptQuest, or linear programming to continually improve results of each trial. With genetic algorithms, each possible solution becomes an independent "organism" that can "breed" with other organisms. The spreadsheet model acts as an environment for the organisms, determining which are "fit" enough to survive based on their results, and occasionally trying “mutations,” or completely new solutions.

3. View Optimization Results. 
After optimization, Evolver can display the results of the original, best, and last solution on your entire model, updating it with each scenario in a single click. This makes it easy to decide the best course of action. You can also generate reports directly in Excel for an optimization summary, log of all simulations, and log of progress steps.

Excel Ease of Use

Evolver is a true add-in to Microsoft Excel, integrating completely with your spreadsheet. Define your models, adjust your settings, run optimizations, monitor progress, and generate reports – while never leaving Excel. Streamlined dialog boxes mean fewer open windows to navigate.

Evolver Features and Benefits
FEATURESBENEFITS
 
Genetic algorithm optimization Find the best global solution to complex, real-life problems
OptQuest solving engine The OptQuest engine integrates Tabu Search, Neural Networks, Scatter Search, and Linear/Integer Programming into a single composite method. It provides great results – and quickly – on many types of models.
100% Excel calculations Highest level of computation accuracy
INTERFACE  
Seamless integration into Microsoft Excel Never leave your spreadsheet; get up to speed quickly
Streamlined interface Fewer nested dialogs and fast model setup
MODEL DEFINITION  
Ranges for adjustable cells and constraints Streamlined model setup and editing
Six solving methods Always have the best method for different types of problems
Discrete adjustable cells Specify increments (such as batches of 10) within adjustable cells ranges, improving accuracy for many types of models. Also speeds up optimization.
OPTIMIZATION  
Progress window At-a-glance status and handy playback controls
Evolver Watcher Monitor progress toward best solutions
Genetic algorithms Find the best global solution while avoiding getting caught in local, “hill-climbing” solutions
OptQuest solving engine The OptQuest engine integrates Tabu Search, Neural Networks, Scatter Search, and Linear/Integer Programming into a single composite method. It provides great results – and quickly – on many types of models.
Efficient Frontier Analysis Especially useful in financial analysis, Efficient Frontiers determine the optimal return that can be expected from a portfolio at a given level of risk
Automatic selection of solving engine Saves time and improves accuracy by automatically using the most appropriate engine for your model.
Efficient constraint handling With OptQuest models, RISKOptimizer will not attempt solutions that fail constraints, make optimizations faster. Non-linear constraints are also faster.
Genetic operators Optimization results fast
REPORTING  
Original, Best, Last model updating Instantly see the effects of three solutions on your entire model
Reports in Excel Save and share optimization and simulation data
MORE  
Application Settings dialog Define a wide range of default settings for all models
Excel Developer Kit (XDK) Automate and customize Evolver through a complete library of commands and functions for VBA

Two Editions to Meet Your Needs

Evolver is available in Professional and Industrial editions. The Professional edition allows up to 250 adjustable variables per model, while the Industrial edition allows unlimited variables. Use Evolver Industrial for your largest models where you can control hundreds or thousands of adjustable cells.