Mixed-Integer linear Programming (MIP) plays a central role in modeling difficult-to-solve (NP-hard) combinatorial problems. However, the exact solution of the resulting models often cannot be carried out for the problem sizes of interest in real-world applications, hence one is interested in effective heuristic methods. Although several heuristic and metaheuristic frameworks have been proposed...

As a new margin-based classifier, ψ-learning shows great potential for high accuracy. However, the optimization of ψ-learning involves non-convex minimization and is very challenging to implement. In this article, we convert the optimization of ψ-learning into a mixed integer programming (MIP) problem. This enables us to utilize the state-of-art algorithm of MIP to solve ψ-learning. Moreover, t...

Recent work on solving job-shop scheduling problems with earliness and tardiness costs has led to several hybrid algorithms that are more effective than any one method alone. In particular, these hybrid methods have been found to be more effective than pure mixed integer programming (MIP) approaches. This paper takes a fresh look at MIP formulations in light of several new MIP strategies for pr...

Mixed Integer Programming (MIP) models are known to be sensitive to slight changes. In this study, we measure the perturbation to a production plan that occurs when re-planning is carried-on due to new orders arrival. Perturbation level is measured using well known metrics: (1) the Hamming distance, (2) the edit distance, and (3) the Damerau-Levenshtein distance. We propose three alternative fo...

We propose a new approach for search tree exploration in the context of combinatorial optimization, specifically Mixed Integer Programming (MIP), that is based on UCT, an algorithm for the multi-armed bandit problem designed for balancing exploration and exploitation in an online fashion. UCT has recently been highly successful in game tree search. We discuss the differences that arise when UCT...

The fixed-charge Capacitated Multi-commodity Network Design (CMND) is a well-known problem of both practical and theoretical significance. Network design models represent a wide variety of planning and operation management issues in transportation telecommunication, logistics, production and distribution. In this paper, Ant Colony Optimization (ACO) based neighborhoods are proposed for CMND pro...

in this paper the real-world occurrence of the multiple-product multiple-constraint single period newsboy problem with two objectives, in which there is incremental discounts on the purchasing prices, is investigated. the constraints are the warehouse capacity and the batch forms of the order placements. the first objective of this problem is to find the order quantities such that the expected ...

this paper uses the l1−norm and the concept of the non-dominated vector, topropose a method to find a well-dispersed subset of non-dominated (wdsnd) vectorsof a multi-objective mixed integer linear programming (momilp) problem.the proposed method generalizes the proposed approach by tohidi and razavyan[tohidi g., s. razavyan (2014), determining a well-dispersed subset of non-dominatedvectors of...

In this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). No set-up is necessary between jobs belonging to the same family. A set-up must be scheduled when switching from the processing of family i jobs to those of another family j, i  j, the duration of this set-up being the sequ...

In both industry and the research literature, mixed integer programming (MIP) is often the default approach for solving scheduling problems. In this paper we present and evaluate four MIP formulations for the classical job shop scheduling problem (JSP). While MIP formulations for the JSP have existed since the 1960s, it appears that comprehensive computational studies have not been performed si...