We present sufficient conditions under which thermal generators can be aggregated in mixed-integer linear programming (MILP) formulations of the unit commitment (UC) problem, while maintaining feasibility and optimality for the original disaggregated problem. Aggregating thermal generators with identical characteristics (e.g., minimum/maximum power output, minimum up/down-time, and cost curves)...

The robust p-median problem in changing networks is a version of known discrete p-median problem in network with uncertain edge lengths where uncertainty is characterised by given interval. The uncertainty in edge lengths may appear in travel time along the edges in any network location problem. Several possible future scenarios with respect to the lengths of edges are presented. The planner wi...

In this paper, we present an analysis of the strength of sparse cutting-planes for mixed integer linear programs (MILP) with sparse formulations. We examine three kinds of problems: packing problems, covering problems, and more general MILPs with the only assumption that the objective function is non-negative. Given a MILP instance of one of these three types, assume that we decide on the suppo...

It is well known that the combination of clock skew scheduling and delay insertion can achieve the lower bound of sequential timing optimization. Previous works focus on the minimization of required inserted delay. However, from the viewpoint of design closure, minimizing the number of inserted buffers is also very important. In this paper, we propose an MILP (mixed integer linear programming) ...

Among the hardest Mixed-Integer Linear Programming (MILP) problems, the ones that exhibit a symmetric nature are particularly important in practice, as they arise in both theoretical and practical combinatorial optimization problems. A theoretical concept that generalizes the notion of symmetry is that of dominance. This concept, although known since a long time, is typically not used in genera...

Tactical planning MILP models for fast moving consumer goods companies are often intractable for realistic applications containing thousands of Stock-Keeping Units (SKUs). Decomposition methods can be applied to these MILP models to allow realistic cases to be optimized. In this paper we present a Multi-SKU decomposition algorithm based on decomposing the full scale MILP model into submodels co...

This paper focuses on optimal path planning for vehicles in known environments. Previous work has presented mixed integer linear programming (MILP) formulations, which suffer from scalability issues as the number of obstacles, and hence the number of integer variables, increases. In order to address MILP scalability, a novel three-stage algorithm is presented which first computes a desirable pa...

Component deployment is a combinatorial optimisation problem in software engineering that aims at finding the best allocation of software components to hardware resources in order to optimise quality attributes, such as reliability. The problem is often constrained due to the limited hardware resources, and the communication network, which may connect only certain resources. Due to the non-line...

Abstract We consider the problem of scheduling under demand uncertainty a multiproduct batch plant represented through the State Task Network. Given a scheduling horizon consisting of several time-periods in which product demands are placed, the objective is to select a schedule that maximizes the expected profit. We present a multistage stochastic Mixed Integer Linear Programming (MILP) model,...

The huge time and memory complexities of utilizing bitbased division property, which was first presented by Todo and Morri at FSE 2016, bothered cryptographers for quite some time and it had been solved by Xiang et al. at ASIACRYPT 2016. They applied MILP method to search integral distinguisher based on division property, and used it to analyze six lightweight block ciphers. Later on, Sun et al...