A search strategy that improves an existing feasible solution by changing its selected elements.
Repeated solution modification is a heuristic search strategy that starts with an existing feasible solution and changes its selected elements to generate improved candidates. It avoids rebuilding every solution from scratch and supports approximate search when exhaustive approaches are impractical. section 2.3
A cargo-bike solution can be represented as a binary selection vector, such as (1,1,0,1,0,1,1,1,1,1), and treated as the feasible starting point for modification. section 2.3
How Optimization Algorithms: AI techniques for design, planning, and control problems covers it
How deep it goes
Defines the strategy and names representative algorithms, but does not detail their modification operators or iteration procedures.
Examples
Uses a cargo-bike package-selection vector as an example of an existing feasible solution.
What it assumes
Assumes a defined optimization problem and at least one feasible solution that can be represented and changed.
What you can do after
Evaluate or understand how heuristic algorithms improve candidate solutions through repeated changes.
How it connects
Distinguishes repeated solution construction and repeated solution recombination within heuristic and metaheuristic search.
repeated solution constructioncontrasts with · A search strategy that generates candidate solutions incrementally by repeatedly adding elements to a partial solution.
repeated solution recombinationcontrasts with · A search strategy that combines parts of existing solutions to construct new candidate solutions.
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