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Forest harvest scheduling = from linear programming to heuristic search /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Forest harvest scheduling/ by Pete Bettinger.
其他題名:	from linear programming to heuristic search /
作者:	Bettinger, Pete.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xxv, 268 p. :ill. (some col.), digital ;24 cm.
內容註:	Chapter 1. Introduction -- 1. Introduction. -- 2. The Forest Harvest Scheduling Optimization Problem. -- 3. Classic and Contemporary Influences on Forest Harvest Scheduling. -- 4. Solving Forest Harvest Scheduling Assignment Problems. -- 5. Harvest Scheduling Search Behavior. -- 6. Difficulty in Developing High Quality Solutions to Mathematical Problems. -- 7. Summary.
Contained By:	Springer Nature eBook
標題:	Logging - Mathematical models. -
電子資源:	https://doi.org/10.1007/978-3-031-89432-9
ISBN:	9783031894329

Forest harvest scheduling = from linear programming to heuristic search /
Bettinger, Pete.

Forest harvest schedulingfrom linear programming to heuristic search /[electronic resource] :by Pete Bettinger. - Cham :Springer Nature Switzerland :2025. - xxv, 268 p. :ill. (some col.), digital ;24 cm. - Springer texts in business and economics,2192-4341. - Springer texts in business and economics..

Chapter 1. Introduction -- 1. Introduction. -- 2. The Forest Harvest Scheduling Optimization Problem. -- 3. Classic and Contemporary Influences on Forest Harvest Scheduling. -- 4. Solving Forest Harvest Scheduling Assignment Problems. -- 5. Harvest Scheduling Search Behavior. -- 6. Difficulty in Developing High Quality Solutions to Mathematical Problems. -- 7. Summary.

This book provides a synthesis of methods that have been used in both practice and research to develop forest harvest schedules (plans of action) and to assess alternative policy scenarios. Beginning with exact mathematical methods (linear, mixed integer, and goal programming), the book provides a brief history of their conception, followed by an approachable description of the processes commonly employed to search a solution space for the optimal solution to a problem. Hill-climbing, random search, and binary search processes are then described as relatively simple alternatives to the exact methods. Heuristic search processes (threshold accepting, simulated annealing, tabu search, and genetic algorithms) are then described as semi-rational, biased alternatives to solving forest harvest scheduling problems. The closing remarks of the book provide context for the use of forest harvest scheduling in addressing today's contemporary forest management issues. In addition to a set of common-sense principles that are introduced throughout the book, provided in the book is a fifty-question exam associated with the content introduced.

ISBN: 9783031894329

Standard No.: 10.1007/978-3-031-89432-9doiSubjects--Topical Terms:

3785952
Logging
--Mathematical models.

LC Class. No.: HD9750.5

Dewey Class. No.: 634.98

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520 $a This book provides a synthesis of methods that have been used in both practice and research to develop forest harvest schedules (plans of action) and to assess alternative policy scenarios. Beginning with exact mathematical methods (linear, mixed integer, and goal programming), the book provides a brief history of their conception, followed by an approachable description of the processes commonly employed to search a solution space for the optimal solution to a problem. Hill-climbing, random search, and binary search processes are then described as relatively simple alternatives to the exact methods. Heuristic search processes (threshold accepting, simulated annealing, tabu search, and genetic algorithms) are then described as semi-rational, biased alternatives to solving forest harvest scheduling problems. The closing remarks of the book provide context for the use of forest harvest scheduling in addressing today's contemporary forest management issues. In addition to a set of common-sense principles that are introduced throughout the book, provided in the book is a fifty-question exam associated with the content introduced.
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