We describe a tabu search (TS) approach for solving general zero-one mixed integer programming (MIP) problems that exploits the extreme point property of zero-one solutions. Specialized choice rules and aspiration criteria are identified for the problems, expressed as functions of integer infeasibility measures and objective function values. The first-level TS mechanisms are then extended with ...

Abstract Despite their great success in recent years, neural networks have been found to be vulnerable adversarial attacks. These attacks are often based on slight perturbations of given inputs that cause them misclassified. Several methods proposed formally prove robustness a network against such However, these typically give rise high computational demands, which severely limit scalability. R...

much research hasn’t been done in the area of project selection in the public sector. in this paper, we tried to choose projects in the public sector, and a linear programming model is presented. in an effort to build the model, the decision criteria were identified using the delphi method and then the criteria were reviewed at conceptual combining. the model was constructed in a linear, goal a...

Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss dec...

We introduce a new optimization framework to maximize the expected spread of cascades in networks. Our model allows a rich set of actions that directly manipulate cascade dynamics by adding nodes or edges to the network. Our motivating application is one in spatial conservation planning, where a cascade models the dispersal of wild animals through a fragmented landscape. We propose a mixed inte...

This paper deals with lot sizing and scheduling for a single-stage, single-machine production system where setup costs and times are sequence dependent. A large-bucket mixed integer programming (MIP) model is formulated which considers only e$cient sequences. A tailor-made enumeration method of the branch-and-bound type solves problem instances optimally and e$ciently. The size of solvable case...

A new mixed-integer programming (MIP) formulation is presented for the production planning of single-stage multi-product processes. The problem is formulated as a multi-item capacitated lot-sizing problem in which (a) multiple items can be produced in each planning period, (b) sequence-independent set-ups can carry over from previous periods, (c) set-ups can cross over planning period boundarie...

This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the mo...

The International Space Station poses very challenging issues from the logistic point of view. Its on-orbit stay is to be significantly extended in the near future and ever increasing experimental activity in microgravity is expected, giving rise to a renewed interest in the related optimization aspects. A permanent logistic support is necessary to guarantee its operational working, as well as ...

In this paper we show that optimization of a family of “maximum score type” estimators can be effectively reformulated as a Mixed Integer Programming (MIP) problem. The maximum score type family includes Manski’s classic maximum score estimator, but also more recently proposed estimators that optimize profit, utility and absolute deviation objective functions, all of which are similarly irregul...