Primal Heuristics in SCIP - ZIB

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Algorithm 1. ¯x ← LP optimum; 2. Fix all integral variables: xi := ¯xi ∀i : ¯xi ∈; 3. Reduce domain of fractional variables: xi ∈ {⌊¯xi⌋; ⌈¯xi⌉}; 4. Solve the resulting subMIP Rens: An LNS Rounding Heuristic 18 / 34
Algorithm 1. ¯x ← LP optimum; 2. Fix all integral variables: xi := ¯xi ∀i : ¯xi ∈; 3. Reduce domain of fractional variables: xi ∈ {⌊¯xi⌋; ⌈¯xi⌉}; 4. Solve the resulting subMIP Rens: An LNS Rounding Heuristic 18 / 34
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DFG Research Center MATHEON Mathema
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1 Introduction Basics Integration I
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Exact methods ⊲ Branch-And-Bound
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Page 13 and 14:
Why use heuristics inside an exact
Page 15 and 16: 1 Introduction Basics Integration I
Page 17 and 18: Domain Propagation Solve LP Constra
Page 19 and 20: Primal Heuristics Domain Propagatio
Page 21 and 22: Two main categories ⊲ Start heuri
Page 27 and 28: Five main approaches ⊲ Rounding a
Page 29 and 30: Statistics & points ⊲ Variables
Page 49 and 50: 1 Introduction Basics Integration I
Page 51 and 52: Guideline: Stay feasible! Features
Page 63 and 64: Algorithm 1. ¯x ← LP optimum; 2.
Page 65: Algorithm 1. ¯x ← LP optimum; 2.
Page 69 and 70: Observations Rens: An LNS Rounding
Page 71 and 72: Idea ⊲ Alternately solve the LP a
Page 73 and 74: Algorithm 1. Solve LP; The Feasibil
Page 83 and 84: Objective Feasibility Pump (Achterb
Page 85 and 86: Other objective divers ⊲ Objectiv
Page 87 and 88: LNS heuristics Idea: Create subMIP
Page 89 and 90: Combinatorial heuristics ⊲ 1-Opt
Page 95 and 96: Some tips and tricks ⊲ Use limits
Page 97 and 98: Some tips and tricks ⊲ Use limits
Page 99 and 100: Single heuristics Remarks & Conclus
Page 101 and 102: Single heuristics Remarks & Conclus
Page 103: DFG Research Center MATHEON Mathema
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Primal Heuristics in SCIP - ZIB

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