63 citations · 291 across the 19 of their papers we have counts for
19 papers
Mixed-Integer Linear Programming Approximations for the Stochastic Knapsack
Roberto Rossi, Steven D. Prestwich, S. Armagan Tarim
We develop mathematical programming approximations to tackle the stochastic knapsack problem. In this problem, the decision maker considers items for which either weights or values…
On the stochastic inventory problem under order capacity constraints
Roberto Rossi, Zhen Chen, S. Armagan Tarim
We consider the single-item single-stocking location stochastic inventory system under a fixed ordering cost component. A long-standing problem is that of determining the structure…
A hybrid estimation of distribution algorithm for joint stratification and sample allocation
Mervyn O'Luing, Steven Prestwich, S. Armagan Tarim
In this study we propose a hybrid estimation of distribution algorithm (HEDA) to solve the joint stratification and sample allocation problem. This is a complex problem in which ea…
Combining K-means type algorithms with Hill Climbing for Joint Stratification and Sample Allocation Designs
Mervyn O'Luing, Steven Prestwich, S. Armagan Tarim
In this paper we combine the k-means and/or k-means type algorithms with a hill climbing algorithm in stages to solve the joint stratification and sample allocation problem. This i…
Computing Optimal (R, s, S) Policy Parameters by a Hybrid of Branch-and-Bound and Stochastic Dynamic Programming
Andrea Visentin, Steven Prestwich, Roberto Rossi +1
A well-know control policy in stochastic inventory control is the (R, s, S) policy, in which inventory is raised to an order-up-to-level S at a review instant R whenever it falls b…
A Simulated Annealing Algorithm for Joint Stratification and Sample Allocation Designs
Mervyn O'Luing, Steven Prestwich, S. Armagan Tarim
This study combines simulated annealing with delta evaluation to solve the joint stratification and sample allocation problem. In this problem, atomic strata are partitioned into m…
A recursion-free functional approximation for the dynamic inventory problem
Onur A. Kilic, S. Armagan Tarim
We consider the dynamic inventory problem with non-stationary demands. It has long been known that non-stationary (s, S) policies are optimal for this problem. However, finding opt…
Declarative Statistics
Roberto Rossi, Özgür Akgün, Steven Prestwich +1
In this work we introduce declarative statistics, a suite of declarative modelling tools for statistical analysis. Statistical constraints represent the key building block of decla…
Stochastic Constraint Programming as Reinforcement Learning
Steven Prestwich, Roberto Rossi, Armagan Tarim
Stochastic Constraint Programming (SCP) is an extension of Constraint Programming (CP) used for modelling and solving problems involving constraints and uncertainty. SCP inherits e…
Computing non-stationary policies using mixed integer linear programming
Mengyuan Xiang, Roberto Rossi, Belen Martin-Barragan +1
This paper addresses the single-item single-stocking location stochastic lot sizing problem under the policy. We first present a mixed integer non-linear programming (MIN…
The BIN_COUNTS Constraint: Filtering and Applications
Roberto Rossi, Özgür Akgün, Steven Prestwich +1
We introduce the BIN_COUNTS constraint, which deals with the problem of counting the number of decision variables in a set which are assigned values that lie in given bins. We illu…
Statistical Constraints
Roberto Rossi, Steven Prestwich, S. Armagan Tarim
We introduce statistical constraints, a declarative modelling tool that links statistics and constraint programming. We discuss two statistical constraints and some associated filt…
Piecewise linear approximations of the standard normal first order loss function
Roberto Rossi, S. Armagan Tarim, Steven Prestwich +1
The first order loss function and its complementary function are extensively used in practical settings. When the random variable of interest is normally distributed, the first ord…
Forecasting Intermittent Demand by Hyperbolic-Exponential Smoothing
S. D. Prestwich, S. A. Tarim, R. Rossi +1
Croston's method is generally viewed as superior to exponential smoothing when demand is intermittent, but it has the drawbacks of bias and an inability to deal with obsolescence,…
A unified modeling approach for the static-dynamic uncertainty strategy in stochastic lot-sizing
Roberto Rossi, Onur A. Kilic, S. Armagan Tarim
In this paper, we develop mixed integer linear programming models to compute near-optimal policy parameters for the non-stationary stochastic lot sizing problem under Bookbinder an…
Confidence-based Reasoning in Stochastic Constraint Programming
Roberto Rossi, Brahim Hnich, S. Armagan Tarim +1
In this work we introduce a novel approach, based on sampling, for finding assignments that are likely to be solutions to stochastic constraint satisfaction problems and constraint…
A note on Tempelmeier's β-service measure under non-stationary stochastic demand
Roberto Rossi, S. Armagan Tarim, Onur A. Kilic
Tempelmeier (2007) considers the problem of computing replenishment cycle policy parameters under non-stationary stochastic demand and service level constraints. He analyses two po…
Scenario-based Stochastic Constraint Programming
Suresh Manandhar, Armagan Tarim, Toby Walsh
To model combinatorial decision problems involving uncertainty and probability, we extend the stochastic constraint programming framework proposed in [Walsh, 2002] along a number o…
Stochastic Constraint Programming: A Scenario-Based Approach
S. Armagan Tarim, Suresh Manandhar, Toby Walsh
To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs contai…