In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two o...

We solve an agent’s optimization problem of meeting demands for cash over time with cash deposited in bank or invested in stock. The stock pays dividends and uncertain capital gains, and a commission is incurred in buying and selling of stock. We use a stochastic maximum principle to obtain explicitly the optimal transaction policy.

Modelling complex systems such as multiple-use reservoirs can be challenging. A legitimate question for scientists and modellers is how best to model their management under uncertain rainfall. This paper studies whether it is worth using a stochastic model that requires more effort than a much simpler deterministic model. Both models are applied to the management of a multiple-use reservoir in ...

Introduction. We study a class of capacitated stochastic lot-sizing inventory control problems with stochastic, non-stationary and correlated demands that evolve over time. Economies of scale and capacity constraints exist in many practical scenarios. However, models with fixed ordering costs and capacity constraints are typically computationally intractable, and even the structure of the optim...

The single-item stochastic inventory control problem is to find an inventory replenishment policy in the presence of independent discrete stochastic demands under periodic review and finite time horizon. In this paper, we prove that this problem is intractable and for any 2 > 0, we design an algorithm with running time polynomial in the size of the problem input and in 1/2, that finds a policy ...

In a market with stochastic investment opportunities, we study an optimal consumption investment problem for an agent with recursive utility of Epstein-Zin type. Focusing on the empirically relevant specification where both risk aversion and elasticity of intertemporal substitution are in excess of one, we characterize optimal consumption and investment strategies via backward stochastic differ...

Most production planning models are deterministic and often assume a linear relation between production volume and production cost. In this paper, we investigate a production planning problem in a steel production process considering the energy consumption cost which is a nonlinear function of the production quantity. Due to the uncertain environment, the production demands are stochastic. Taki...

In this study, we introduce the urban recharging infrastructure design problem with stochastic demands and capacitated recharging stations. Stochastic recharge demands shaped by daily transportation/logistics activity cycles, capacity limitations of recharging stations and users’ route preferences need to be considered simultaneously to address this urgent problem that focus on the inner city t...

The objective of the Vehicle Routing Problem (VRP) is to construct a minimum cost set of vehicle routes that visits all customers and satisfies demands without violating the vehicle capacity constraints. The Stochastic Vehicle Routing Problem (SVRP) results when one or more elements of the VRP are modeled as random variables. In this paper, we present a set-partitioning-based modeling framework...

The vehicle routing problem with stochastic demands and probabilistic distance constraints (VRPSD-PDC) can be defined on a complete and undirected graph G = (V, E), where V = {0, . . . , n} is the vertex set and E = {(v, u) : v, u ∈ V, v ̸= u} is the edge set. Vertices v = 1, . . . , n represent the customers and vertex v = 0 represents the depot. A distance de is associated with edge e = (v, u)...