RsBundle  Diff

// Copyright (c) 2016 Frank Fischer <frank-fischer@shadow-soft.de>
// Copyright (c) 2016, 2017 Frank Fischer <frank-fischer@shadow-soft.de>
//
// This program is free software: you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation, either version 3 of the
// License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful, but

        self.nxt_y.add(&self.cur_y, &self.nxt_d);
        self.nxt_mod = self.master.get_primoptval();
        self.sgnorm = self.master.get_dualoptnorm2().sqrt();
        self.expected_progress = self.cur_val - self.nxt_mod;

        // update multiplier from master solution
        for i in 0..self.problem.num_subproblems() {
            for m in self.minorants[i].iter_mut() {
            for m in &mut self.minorants[i] {
                m.multiplier = self.master.multiplier(m.index);
            }
        }

        debug!("Model result");
        debug!("  cur_val ={}", self.cur_val);
        debug!("  nxt_mod ={}", self.nxt_mod);

            if nxt_ub > descent_bnd {
                // upper bound will produce null-step
                if self.cur_val - nxt_lb > (self.cur_val - self.nxt_mod) * self.params.nullstep_factor.max(0.5) {
                    warn!("Relative precision of returned objective interval enforces null-step.");
                    self.iterinfos.push(IterationInfo::UpperBoundNullStep);
                }
            }
        } else {
        } else if self.cur_val - nxt_lb > 0.8 * (self.cur_val - self.nxt_mod) {
            // TODO: double check with ConicBundle if this test makes sense.
            // lower bound gives already a null step
            if self.cur_val - nxt_lb > 0.8 * (self.cur_val - self.nxt_mod) {
                // subgradient won't yield much improvement
                warn!("Shallow cut (subgradient won't yield much improvement)");
                self.iterinfos.push(IterationInfo::ShallowCut);
            // subgradient won't yield much improvement
            warn!("Shallow cut (subgradient won't yield much improvement)");
            self.iterinfos.push(IterationInfo::ShallowCut);
            }
        }

        debug!("Step");
        debug!("  cur_val    ={}", self.cur_val);
        debug!("  nxt_mod    ={}", self.nxt_mod);
        debug!("  nxt_ub     ={}", self.nxt_val);
        debug!("  descent_bnd={}", descent_bnd);

        // do a descent step or null step
        if nxt_ub <= descent_bnd {
            self.descent_step();
            return Ok(Step::Descent);
            Ok(Step::Descent)
        } else {
            self.null_step();
            return Ok(Step::Null);
            Ok(Step::Null)
        }
    }

    /**
     * Return the bound on the function value that enforces a
     * nullstep.
     *