We develop algorithms for a single machine stochastic appointment sequencing and scheduling problem with waiting time, idle time, and overtime costs. This is a basic stochastic scheduling problem that has been studied in various forms by several previous authors. Applications for this problem cited previously include scheduling of surgeries in an operating room (Denton, 2007, Denton and Gupta,2...

This paper presents a framework for the design and optimization of multi-product batch processes under uncertainty with environmental considerations. The uncertainties and environmental impacts are discussed. The profit and environmental impacts are considered as biobjectives for batch plant design. The problem, thus, is formulated as a multi-objective stochastic programming problem. It can be ...

This paper introduces a new cutting plane method for two-stage stochastic mixed-integer programming (SMIP) called Fenchel decomposition (FD). FD uses a class of valid inequalities termed, FD cuts, which are derived based on Fenchel cutting planes from integer programming. First, we derive FD cuts based on both the first and second-stage variables, and devise an FD algorithm for SMIP and establi...

Last-mile logistics is regarded as an essential yet highly expensive component of parcel logistics. In dense urban environments, this partially caused by inherent inefficiencies due to traffic congestion and the disparity accessibility customer locations. logistics, access hubs are facilities supporting relay-based last-mile activities offering temporary storage locations enabling decoupling fr...

We propose a two-stage stochastic variational inequality model to deal with random variables in variational inequalities, and formulate this model as a two-stage stochastic programming with recourse by using an expected residual minimization (ERM) solution procedure. The solvability, differentiability and convexity of the two-stage stochastic programming and the convergence of its sample averag...

The paper considers solving of linear programming problems with p-order conic constraints that are related to a certain class of stochastic optimization models with risk objective or constraints. The proposed approach is based on construction of polyhedral approximations for p-order cones, and then invoking a Benders decomposition scheme that allows for efficient solving of the approximating pr...

The renowned nursing shortage has attracted much attention from national level law makers, state legislatures, commercial organizations, and researchers due to its direct impact on the quality of patient care. High workloads and undesirable schedules are two major issues that cause nurses’ job dissatisfaction. The focus of this paper is to find nondominated solutions to an integrated nurse staf...

This paper considers the primary and secondary path generation problem in traffic engineering. We first present a standard MILP model. Since its size and integrality gap are very large, we then apply a Benders decomposition to isolate the failure case capacity constraints, related linearisation variables and linearisation constraints. The disaggregated Benders cuts are generated, which is actua...

In-house production or outsourcing are important strategic decisions for planning production and capacity in business organizations. Outsourcing to overseas suppliers is often associated with risk with respect to the quality of the products. Hence, we developed a multi-stage stochastic programming model that takes into account the uncertainty involved in the production of the quality of outsour...