Inverted indexes are typically used in text-based data warehousing, not geographical data warehousing.

Spatial indexes are used to speed up the processing of spatial queries, such as finding all the features within a given region or finding the nearest feature to a given point.

B-trees are not spatial indexes. They are a type of balanced search tree used for indexing data in a relational database.

Temporal indexes are used to speed up the processing of temporal queries, such as finding all the features that changed within a given time period or finding the state of a feature at a given time.

B-trees are not temporal indexes. They are a type of balanced search tree used for indexing data in a relational database.

Attribute indexes are used to speed up the processing of attribute queries, such as finding all the features with a given attribute value or finding the maximum value of an attribute.

R-trees are not attribute indexes. They are a type of spatial index used for indexing data in a geographical data warehouse.

Query optimization is the process of improving the performance of queries by using techniques such as indexing, materialized views, and query rewriting.

Data partitioning is a data management technique, not a query optimization technique.

Cost-based optimization uses statistical information about the data and the query to estimate the cost of executing a query. This information is then used to choose the most efficient execution plan for the query.

Simulated annealing is a heuristic-based optimization technique, not a cost-based optimization technique.

Rule-based optimization applies a set of predefined rules to optimize a query. These rules are typically based on the structure of the query and the characteristics of the data.

Materialized view selection is a cost-based optimization technique, not a rule-based optimization technique.

Heuristic-based optimization uses heuristics to optimize a query. Heuristics are rules of thumb that are used to make decisions about how to optimize a query.

Simulated annealing is a cost-based optimization technique, not a heuristic-based optimization technique.