the aim of this study is to propose a new mixed integer linear programming (milp) model to find the minimum required number of yard cranes, rubber tyred gantry cranes (rtgcs), for completion the total amount of works at the end of planning horizon. in other word, we find the optimal number of yard cranes in a container terminal which completes the total amount of works. the paper supports the p...

research interests have been focused on the concept of penalizing jobs both for being early and for being tardy because not only of modern competitive industrial challenges of providing a variety of products at a very low cost by smoothing productions but also of its increasing and exciting computer applications. here, sequencing approaches of the mixed- model just-in-time production systems is...

Decomposition has proved to be one of the more effective tools for the solution of large-scale problems, especially those arising in stochastic programming. A decomposition method with wide applicability is Benders’ decomposition, and has been applied to both stochastic programming, as well as integer programming problems. However, this method of decomposition relies on convexity of the value f...

In project scheduling under processing times uncertainty, the Anchor-Robust Project Scheduling Problem is to find a baseline schedule of bounded makespan and max-weight subset jobs whose starting are guaranteed. The problem was proven NP-hard even for budgeted uncertainty. present work we design mixed-integer programming (MIP) formulations that valid variety uncertainty sets encompassing A new ...

Supply Chain Management (SCM) decisions can be considered at different levels of detail. At a strategic level they apply to the architecture in the supply chain, at the tactical level to transport fleet selection, selection of supply sources and distribution, and at the operational level, to the distribution of supplies and route selection. Many models of decision-making SCM have been developed...

Existing algorithms for learning optimal decision trees can be put into two categories: based on the use of Mixed Integer Programming (MIP) solvers and dynamic programming (DP) itemsets. While DP are fastest, their main disadvantage compared to MIP-based approaches is that amount memory these may require find an solution not bounded. Consequently, some datasets only executed machines with large...

In Mixed Integer Linear Programming (MIP), a (strong) backdoor is ``small" subset of an instance's integer variables with the following property: in branch-and-bound procedure, instance can be solved to global optimality by branching only on backdoor. Constructing datasets pre-computed backdoors for widely used MIP benchmark sets or particular problem families enable new questions around novel ...

This paper presents a hybrid of a general heuristic framework and a general purpose mixed-integer programming (MIP) solver. The framework is based on local search and an adaptive procedure which chooses between a set of large neighborhoods to be searched. A mixed integer programming solver and its built-in feasibility heuristics is used to search a neighborhood for improving solutions. The gene...

This paper considers a scheduling problem with component availability constraints in a supply chain consisting of two manufacturing facilities and a merge-in-transit facility. Three mixed-integer programming (MIP) models and a constraint programming (CP) model are compared in an extensive numerical study. Results show that when there are no components shared among the two manufacturers, the MIP...