A facility with front room and back room operations has the option of hiring specialized or, more expensive, cross-trained workers. Assuming stochastic customer arrival and service times, we seek a smallest-cost combination of cross-trained and specialized workers satisfying constraints on the expected customer waiting time and expected number of workers in the back room. A constraint programmi...

Influence maximization aims at identifying a limited set of key individuals in (social) network which spreads information based on some propagation model and maximizes the number reached. We show that influence probabilistic independent cascade can be modeled as stochastic maximal covering location problem. A reformulation Benders decomposition is proposed relation between obtained optimality c...

This paper describes a Benders decomposition algorithm capable of efficiently solving large-scale instances of the well-known multi-commodity capacitated network design problem with demand uncertainty. The problem is important because it models many real-world applications, including telecommunications, transportation, and logistics. This problem has been tackled in the literature with meta-heu...

Facing supply uncertainty of bulky wastes, the capacitated multi-product stochastic network design model for bulky waste recycling is proposed in this paper. The objective of this model is to minimize the first-stage total fixed costs and the expected value of the second-stage variable costs. The possibility of operation costs and transportation costs for bulky waste recycling is considered ...

Multistage stochastic programs with interstage independent random parameters have recourse functions that do not depend on the state of the system. Decomposition-based algorithms can exploit this structure by sharing cuts (outer-linearizations of time recourse function) among different scenario subproblems at the same stage. The ability to share cuts is necessary in practical implementations of...

Neodymium-iron-boron (NdFeB) magnets are the most powerful per unit volume sold in commercial market. Despite increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including COVID-19 pandemic have caused significant uncertainties supply NdFeB magnets. Therefore, this study aims to alleviate risk of shortage containing critical materials, ...

This dissertation analyzes three scheduling problems motivated by real life situations. In many manufacturing and service industries, scheduling is an important decision-making process. Unfortunately, scheduling problems are often computationally challenging to solve, and even modeling a scheduling problem can be difficult. Chapter 2 considers single-facility non-preemptive scheduling problems ...

T disjunctive decomposition (D2) algorithm has emerged as a powerful tool to solve stochastic integer programs. In this paper, we consider two-stage stochastic integer programs with binary first-stage and mixedbinary second-stage decisions and present several computational enhancements to D2. First, we explore the use of a cut generation problem restricted to a subspace of the variables, which ...

Benders is one of the most famous decomposition tools for Mathematical Programming, and it is the method of choice e.g., in Mixed-Integer Stochastic Programming. Its hallmark is the capability of decomposing certain types of models into smaller subproblems, each of which can be solved individually to produce local information (notably, cutting planes) to be exploited by a centralized “master” p...

in order to implement the cellular manufacturing system in practice, some essential factors should be taken into account. in this paper, a new mathematical model for cellular manufacturing system considering different production factors including alternative process routings and machine reliability with stochastic arrival and service times in a dynamic environment is proposed. also because of t...