A fast taboo search algorithm for the job shop problem
Management Science
Tabu search and finite convergence
Discrete Applied Mathematics
Tabu Search
A Heuristic for Boolean Optimization Problems
Journal of Heuristics
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Mathematical Programming: Series A and B
Parametric tabu-search for mixed integer programs
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
Pivot, Cut, and Dive: a heuristic for 0-1 mixed integer programming
Journal of Heuristics
Infeasible/feasible search trajectories and directional rounding in integer programming
Journal of Heuristics
Foundation-penalty cuts for mixed-integer programs
Operations Research Letters
International Journal of Applied Metaheuristic Computing
Computers and Operations Research
International Journal of Applied Metaheuristic Computing
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Recent metaheuristics for mixed integer programming have included proposals for introducing inequalities and target objectives to guide this search. These guidance approaches are useful in intensification and diversification strategies related to fixing subsets of variables at particular values. The authors' preceding Part I study demonstrated how to improve such approaches by new inequalities that dominate those previously proposed. In Part II, the authors review the fundamental concepts underlying weighted pseudo cuts for generating guiding inequalities, including the use of target objective strategies. Building on these foundations, this paper develops a more advanced approach for generating the target objective based on exploiting the mutually reinforcing notions of reaction and resistance. The authors demonstrate how to produce new inequalities by "mining" reference sets of elite solutions to extract characteristics these solutions exhibit in common. Additionally, a model embedded memory is integrated to provide a range of recency and frequency memory structures for achieving goals associated with short term and long term solution strategies. Finally, supplementary linear programming models that exploit the new inequalities for intensification and diversification are proposed.