On the unimodality of METRIC Approximation subject to normally distributed demands

METRIC Approximation is a popular model for supply chain management. We prove that it has a unimodal objective function when the demands of the n retailers are normally distributed. That allows us to solve it with a convergent sequence. This optimization method leads us to a closed-form equation of computational complexity O(n). Its solutions are … Read more

Asymptotic optimality of Tailored Base-Surge policies in dual-sourcing inventory systems

Dual-sourcing inventory systems, in which one supplier is faster (i.e. express) and more costly, while the other is slower (i.e. regular) and cheaper, arise naturally in many real-world supply chains. These systems are notoriously difficult to optimize due to the complex structure of the optimal solution and the curse of dimensionality, having resisted solution for … Read more

Optimality gap of constant-order policies decays exponentially in the lead time for lost sales models

Inventory models with lost sales and large lead times have traditionally been considered intractable due to the curse of dimensionality. Recently, Goldberg and co-authors laid the foundations for a new approach to solving these models, by proving that as the lead time grows large, a simple constant-order policy is asymptotically optimal. However, the bounds proven … Read more

An SDP approach for multiperiod mixed 0–1 linear programming models with stochastic dominance constraints for risk management

In this paper we consider multiperiod mixed 0–1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer linear recourse as the risk measure. The SDC strategy extends the existing literature to the multistage case and includes both first-order and second-order constraints. We propose a stochastic … Read more

Robust newsvendor problem with autoregressive demand

This paper explores the classic single-item newsvendor problem under a novel setting which combines temporal dependence and tractable robust optimization. First, the demand is modeled as a time series which follows an autoregressive process AR(p), p>= 1. Second, a robust approach to maximize the worst-case revenue is proposed: a robust distribution-free autoregressive forecasting method, which … Read more

Parallel Large-Neighborhood Search Techniques for LNG Inventory Routing

Liquefied natural gas (LNG) is estimated to account for a growing portion of the world natural gas trade. For profitable operation of a capital intensive LNG project, it is necessary to optimally design various aspects of the supply chain associated with it. Of particular interest is optimization of ship schedules and the inventories on the … Read more

An inventory model with shortages for imperfect items using substitution of two products

Inventory models with imperfect quality items are studied by researchers in past two decades. Till now none of them have considered the effect of substitutions to cope up with shortage and avoid lost sales. This paper presents an EOQ approach for inventory system with shortages and two types of products with imperfect quality by one … Read more

Robust Stable Payoff Distribution in Stochastic Cooperative Games

Cooperative games with transferable utilities belong to a branch of game theory where groups of players can enter into binding agreements and form coalitions in order to jointly achieve some objectives. In a cooperative setting, one of the most important questions to address is how to establish a payoff distribution among the players in such … Read more

Bound Improvement for LNG Inventory Routing

Liquefied Natural Gas (LNG) is steadily becoming a common mode for commercializing natural gas. In this paper, we develop methods for improving both lower and upper bounds for a previously stated form of an LNG inventory routing problem. A Dantzig-Wolfe-based decomposition approach is developed for LNG inventory routing problem (LNG-IRP) attempting to overcome poor lower … Read more

Constraint Programming for LNG Ship Scheduling and Inventory Management

We propose a constraint programming approach for the optimization of inventory routing in the liquefied natural gas industry. We present two constraint programming models that rely on a disjunctive scheduling representation of the problem. We also propose an iterative search heuristic to generate good feasible solutions for these models. Computational results on a set of … Read more