The parameter configuration problem consists of finding a that gives particular algorithm the best performance. This paper introduces new multi-phase tuner based on iterated local search meta-heuristic. addresses for deterministic MILP solvers are used to solve challenging industrial optimization problems. Further, proposed offers strategy three ideas. First, instead tuning in entire space indu...

Mixed logical linear programming MLLP is an extension of mixed integer linear pro gramming MILP It can represents the discrete elements of a problem with logical propo sitions and provides a more natural modeling framework than MILP It can also have computational advantages partly because it eliminates integer variables when they serve no purpose provides alternatives to the traditional continu...

The problem of selecting processes and capacity expansion policies for a chemical complex consisting of continuous chemical processes can be formulated as a multiperiod mixed integer linear programming problem. Based on a variable disaggregation technique that exploits lot sizing substructures, we propose two reformulations of the conventional MILP model. The first one is an NLP reformulation t...

Many large-scale scientific applications need to aggregate large amounts of data from multiple distributed sites to a centralized facility. We call such a request as a Data-Aggregation Request (DAR). In this study, we investigate the novel problem of on-demand DAR provisioning over a wavelength-division multiplexing (WDM) backbone network. We provide a mathematical formulation for our problem a...

Abstract In this work, a strict MILP formulation for the supply-chain pick-up and delivery problem with transshipments is presented (SC-PDP-T). This problem adds the option for transferring goods from one vehicle to another. This additional flexibility is very attractive for the optimal management of supply chains. Based on the novel features of the SC-PDP-T, this work addresses the major model...

This paper studies a scenario-based mean-CVaR portfolio optimization problem with nonconvex transaction costs. This problem can be framed as a mixed integer linear programming (MILP) problem by making a piecewise linear approximation of the transaction cost function. Nevertheless, large-scale problems are computationally intractable even with state-of-the-art MILP solvers. To efficiently solve ...