Cooperative Search Techniques

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Paper review of ENGG6140
Cooperative Search Techniques
Shaw Vincent
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Outline

• Introduction of general Cooperative Search
  Techniques
• Introduction of TECHS approach
• Introduction of JSSP (Job-Shop Scheduling
  problem)
• TECHS Approach
• Experiments
• Related Approach
• Conclusion

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Introduction of general Cooperative Search
Techniques
What is Cooperative Search Technique?

• Cooperative search is a parallel strategy for
  search algorithms where parallelism is obtained
  by concurrently executing several search
  programs.
• The solution space is implicitly decomposed
  according to the search strategy of each program.
  
• The programs cooperate by exchanging information
  on previously explored regions of the solution
  space.

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Introduction of general Cooperative Search
Techniques
Why we need Cooperative Search Techniques?

• Different search techniques have different
  strengths and weaknesses.
• Genetic Algorithm good at exploration, but not
  good for local search
• Simulated Annealing capable of producing near
  optimal solution, but consumes huge amounts of
  time.
• Tabu searchcapable to explore and exploit, but
  requires lots of parameter tuning

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Introduction of TECHS approach
What is TECHS?
TECHS is Teams for Cooperative Heterogeneous
Search
(Multi-agent based approach,Genetic Algorithms
Branch-and-Bound method)
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Introduction of TECHS approach

• What are search agents?
• A search agent is a search process with
  additional communication abilities.

• Two components in search process
• Search model consists of a set of possible
  search states and a transition relation that
  defines the possible successor states to each
  state.
• Search control select for a search state exactly
  one of the possible successor states defined by
  the transition relation.

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Introduction of TECHS approach
What are possible types of information to
exchange?

• Positive information the information that helps
  finding a solution to a given instance of a
  search problem.
• e.g information intended to direct the search
  towards the search goal.
• Negative information the information that does
  not lead towards finding a solution, but
  characterizes attribute values that are
  definitely not part of a solution.
• e.g information intended to avoid possible steps
  in the search process.

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Introduction of TECHS approach
Why we need referees?
Since each action taken by an agent during its
search results in possible information to
exchange, it is very important to limit the
information that is really exchanged.
Referees Send-referees Receive-referees
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Introduction of TECHS approach
The usage of Referees
Send-referee select information of all types on
the side of the sending agent. Receive-referee
provide an additional filter on the side of the
receiving agent.
By adding send- and receive-referees and
communication channels between the processes, we
get search agents.
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Introduction of TECHS approach
Criteria of Send-referees

• Success-driven
• Parts of search states that enable good
  transitions should be preferred to parts that
  only enabled bad ones.
• Demand-driven
• Rating the information to select w.r.t the
  control strategy of other agents or w.r.t certain
  attributes solutions should have or not have.
• A further criteria
• very unlike that the other agent will find the
  information on its own.

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Introduction of TECHS approach
About data format
In order to communicate information of all types,
data format are needed to represent information.
This format can be used for communication by all
systems. The search systems internally might use
totally different data structure.
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Introduction of TECHS approach
Criteria of Receive-referees

• Try to measure the impact of the information on
  the further search of the agent.
• This is especially important for positive
  information, since it tends to broaden the search
  space if it is not useful.
• Filtering negative information is not so
  critical, but if an agent accumulates too much
  negative information then the selection process
  for the next search steps can become time
  consuming.

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Introduction of TECHS approach
Two phases

• Working phase the agent concentrates on its
  search.
• Cooperation phase Send-referees select
  information to be sent away and Receive-referees
  filters the information received from the other
  agents.

If all agents use the same time interval for
working phases one can organize the information
interchange in a synchronized manner, else it has
to be asynchronous.
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Introduction of TECHS approach
How to use exchanged information?

• Directly be included in the search state of an
  agent.
• Or it can influence the control the agent employs
  in its search. (as parameters of the control)

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Introduction of TECHS approach
Summary of building a TECHS-based search team

• Data format for the different types of
  information must be found.
• The used search systems must be modified to
  provide send-referees with information.
• The search systems must also be modified to
  enable the integration of the information
  selected by their receive-referees into search
  state and search control. (very hard)
• Send- and receive-referees must be developed.

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Introduction of JSSP
Objective To solve JSSP (Job-Shop Scheduling
problem)
Method TECHS
GA
GA
GA
Branch-and-bound
Branch-and-bound
GA
GA
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Introduction of JSSP

• Definition There are n jobs and m machines each
  job comprises a set of operations which must each
  be done on a different machine for different
  specified time.
• Features
• very important practical problem
• being among the worst members of class of
  NP-complete problems.
• It is hard for conventional search-based methods
  to find near-optima in reasonable time.

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Introduction of JSSP
An example
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Introduction of JSSP
Existed methods to solve JSSP

• Job-Shop System
• NY

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Introduction of JSSP
Jop-Shop System

• BB system for solving the JSS problem, implement
  in C.
• BB based search uses and-trees to represent
  search states. Transitions
• close leaves in such a tree, if they represent a
  solution or have a bound that is not better than
  the best currently known solution.
• expand one leaf of the current tree by adding new
  leaves.

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Introduction of JSSP
NY
NY is a GA based on the idea of Nakano and Yamada
which employs a special version of the
Giffler-Thompson algorithm both to create
schedules and in the crossover and mutation
operators.
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TECHS Approach
Central data format Partial Schedule
Full Schedule Partial Schedule

• Full schedule contains for each operation of
  each job the exact start time and that fulfills
  all requirements on the problem.
• Partial schedule consists of a set of ordering
  conditions that are based on two relations
  between operations on a machine.
• op1 gt op2 op1 is performed before op2 (maybe
  other operations between them)
• op1 op2 op2 directly follows op1.

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TECHS Approach
The Send-Referees

• Select information of all types out of the
  current search state and the search sequence
  produced so far.

• Mainly base their selection on the success the
  pieces of information produced by the agent.

• Receiving agents determine the type of the
  send-referee.

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TECHS Approach
BB?BB

• BB agents exchange positive and negative
  information to be integrated into the search
  state.

• Send-referee always selects the best known
  full schedule as the positive
  information, if there has been some change since
  the last cooperation phase.

• Negative information are partial schedules
  describing closed subtrees of the current state.
  The more nodes this subtree has, the more
  important it is to communicate this information.

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TECHS Approach
BB?NY

• Agents using a GA can only use positive
  information to be included into the search state.

• Send-referee selects the partial schedules
  that have the best bound-values as the positive
  information(and have not been communicated
  already).

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TECHS Approach
NY?BB

• Agents using a GA can only produce positive
  information.

BB agents can use the information both as the
control information and as information to be
integrated into the search state.

• The positive information to be integrated into
  the search state is the best individual of the NY
  agent.

• Positive control information are individuals
  representing very good solutions. In addition,
  they should represent different areas of the
  search tree of the receiving agent than its
  currently focused area(they should very
  different).

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Positive control information
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TECHS Approach
NY?NY

• The only type of information exchanged are
  positive individuals to be integrated into the
  current search state.

• Criteria for the selection are quality of the
  solutions and their difference.

• This send-referee was not used in the
  experiments.

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TECHS Approach
The receive-referees

• Filter incoming information in order to select
  information that meet the current needs of their
  search agents.

NY Agent

• Only receives partial schedules to be integrated
  into its search state.

• receive-referee extend partial schedules to full
  ones.

• Criteria used for selection are quality and
  difference.

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TECHS Approach
BB Agent

• Receive-referee filter positive and negative
  information to be integrated and positive control
  information.

• Positive full schedules only the one with
  the highest quality that is higher than the
  quality of the best known solution so far is
  selected.(How does the agent use this info?)

• Negative partial schedules used by the agent
  to close a leaf.
• 
  How?

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Experiments

• Benchmarks stemming from the OR-library.(URL
  http//mscmga.ms.ic.ac.uk/info.html)
  
  
  

• Each experiment, maximal run-time 28800
  seconds(8 hours)

• Working phases125 seconds.

• Communication was synchronized using the
  function of the UNIX socket concept.

• GA agent used 2600 population size.

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Solution quality comparison of the single agents
Vs TECHS team
2010
1515
2010

• TECH team produced better schedules than all
  its agents working alone. The team is always
  better than its best member.

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Comparison of times needed to find comparable
solutions

• In most case, ETCHS produce comparable solution
  in less time.

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Related Approaches

• Most parallelization approaches based on some
  cooperation of search agents employ homogeneous
  agents.

• Injection island GA
• TEAMWORK

• Only a few approaches employ search agents with
  different search models(heterogeneous agents).

• TECHS

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Conclusion

• TECHS presented a cooperation of evolution
  algorithms with systems on other search paradigms.

• TECHS exchange different types of information
  between agents.

• Send/Receive-referees reduces the amount of
  communication while still selecting the important
  information.

• TECHS results in synergetic improvements both in
  quality of the solutions found and time needed to
  find solutions of a certain quality.

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Question?
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Positive full schedule for BB agent
135
148
150
140
145
150
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Negative Information for BB Agent