Job-Shop Scheduling by Simulated Annealing Combined with Deterministic Local Search

: The Job-Shop Scheduling Problem (JSSP) is one of the most difficult NP-hard combinatorial optimization problems. This paper proposes a new method for solving JSSPs based on simulated annealing (SA), a stochastic local search, enhanced by shifting bottleneck (SB), a problem specific deterministic local search. In our method new schedules are generated by a variant of Giffler and Thompson's active scheduler with operation permutations on the critical path. SA selects a new schedule and probabilistically accepts or rejects it. The modified SB is applied to repair the rejected schedule; the new schedule is accepted if an improvement is made. Experimental results showed the proposed method found near optimal schedules for the difficult benchmark problems and outperformed other existing local search algorithms. Key Words: Simulated annealing, shifting bottleneck, job-shop scheduling, heuristics, local search 1. Background Scheduling is allocating shared resources over time to competi..

Marine turtle regional management units 2.0:an updated framework for conservation and research of wide-ranging megafauna species

Delineating spatial boundaries that accurately encompass complex, often cryptic, life histories of highly migratory marine megafauna can be a significant conservation challenge. For example, marine turtles range across vast ocean basins and coastal areas, thus complicating the evaluation of relative impacts of multiple overlapping threats and the creation of coherent conservation strategies. To address these challenges, spatially explicit ‘regional management units’ (RMUs) were developed in 2010 for all marine turtle species, globally. RMUs were intended to provide a consistent framework that organizes conspecific assemblages into units above the level of nesting rookeries and genetic stocks, but below the species level, within regional entities that may share demographic trajectories because they experience similar environmental conditions and other factors. From their initial conception, RMUs were intended to be periodically revised using new information about marine turtle distributions, life history, habitat use patterns, and population structure. Here, we describe the process used to update the 2010 RMU framework by incorporating newly published information and inputs from global marine turtle experts who are members of the IUCN Marine Turtle Specialist Group. A total of 48 RMUs for 6 of 7 marine turtle species and 166 distinct genetic stocks for all 7 species are presented herein. The updated RMU framework reflects a significant advance in knowledge of marine turtle biology and biogeo - graphy, and it provides improved clarity about the RMU concept and its potential applications. All RMU products have been made open access to support research and conservation initiatives worldwide.</p