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In this paper we consider the vehicle routing problem with hard time windows and stochastic service times (VRPTW-ST); in this variant of the classic VRPTW the service times are random variables. In particular, given a set of vehicle routes, some of the actual service times might not lead to a feasible solution, given the customer time windows. We consider a chance-constrained program to model the VRPTW-ST and provide a new set partitioning formulation that includes a constraint on the minimum success probability of the set of vehicle routes. Under some mild conditions, we develop a method to exactly compute the success probability of the routes. We then solve the VRPTW-ST by a branch-price-and-cut algorithm, where the main challenges are in the solution of the subproblems of the column generation procedure. We adapt the dynamic programming algorithm to account for the probabilistic resource consumption by extending the label dimension and by providing new dominance rules. Extensive computational experiments prove the effectiveness of both the solution method and the stochastic model.

In this paper we consider the vehicle routing problem with hard time windows and stochastic service times (VRPTW-ST); in this variant of the classic VRPTW the service times are random variables. In particular, given a set of vehicle routes, some of the actual service times might not lead to a feasible solution, given the customer time windows. We consider a chance-constrained program to model the VRPTW-ST and provide a new set partitioning formulation that includes a constraint on the minimum success probability of the set of vehicle routes. Under some mild conditions, we develop a method to exactly compute the success probability of the routes. We then solve the VRPTW-ST by a branch-price-and-cut algorithm, where the main challenges are in the solution of the subproblems of the column generation procedure. We adapt the dynamic programming algorithm to account for the probabilistic resource consumption by extending the label dimension and by providing new dominance rules. Extensive computational experiments prove the effectiveness of both the solution method and the stochastic model.

In this paper, the integrated planning of production, maintenance, and quality in deteriorating systems is investigated. The production planning part of the model addresses a multi-product lot-sizing problem with deteriorating quality and in quality planning, we discuss the optimal determination of an inspection process that is used to study the hidden state of the system. Considering imperfect maintenance linked to the machine age and with several possibilities for improving the machine conditions, a maintenance plan determines the type of operations to be performed on the machine in each intrusion. These decisions are simultaneously linked to the lot-sizing and quality decisions where the objective function minimizes the total cost of the system. A numerical example and sensitivity analysis of the problem are also presented.

This paper proposes a solution approach based on heuristic methods for a model integrating production planning and maintenance scheduling in imperfect production systems. Performance of population-based heuristics is considerably influenced by the population management tools that are generally aimed to keep the diversity and to force the search process to examine unvisited areas within the solution space. We use genetic algorithm hybridize with a standard tabu search as well as population management strategies to efficiently solve the complicated nonlinear model. Exploiting population data in order to define new solutions from unvisited sections of response space, learning from the population to extract the specifications of promising solutions and maintaining the population diversity are the most important particularities of the proposed approach. Comparing the algorithm with conventional implementation of GA and tabu search, demonstrates its surpassing performance in terms of solution time and quality.

We apply the PHA on Hydro‐Quebec's reservoir system.A long‐term planning horizon is considered.Deterministic and stochastic solutions are compared. Among the numerous methods proposed over the past decades for solving reservoir management problems, only a few are applicable on high‐dimensional reservoir systems (HDRSs). The progressive hedging algorithm (PHA) was rarely used for managing reservoir systems, but this method is a promising alternative to conventionally used methods for managing HDRSs (e.g., the stochastic dual dynamic programming). The PHA is especially well suited when a new stochastic optimization model must be built upon an existing deterministic optimization model (DOM). In such case, scenario subproblems can be resolved using an existing DOM with minor modifications. In previous studies, the PHA was rarely used and only tested on problems covering short‐range planning horizons (2 months with six time periods) where a small number of nonanticipativity constraints (NACs) must be satisfied. Large reservoirs often need to be managed over a much longer planning horizon (1–5 years) containing many tens of time periods. In such case, convergence becomes much more difficult to achieve because of the larger number of NACs to be satisfied. Finding a nonanticipative solution becomes particularly difficult when the input scenarios differ drastically. In this study, we demonstrate the applicability of the PHA for managing HDRSs over long‐term (more than a year) horizons in highly uncertain decision environments. We apply the PHA on Hydro‐Québec's reservoir system over a 92 week (period) horizon. We analyze the performance of the PHA for different penalty parameter values. Deterministic solutions are compared to stochastic solutions.

The linear Bilevel Programming Problem (BLP) is an instance of a linear hierarchical decision process where the lower level constraint set is dependent on decisions taken at the upper level. In this paper we propose to solve this NP-hard problem using an adaptive search method related to the Tabu Search metaheuristic. Numerical results on large scale linear BLPs are presented.

Routing models for packet-switched networks have traditionally been based on the assumption that the offered traffic is Poisson. This is unrealistic since for many applications, real life data streams tend to be extremely “bursty”, contradicting the Poisson assumption. This paper introduces a centralized bifurcated routing optimization model for networks with significantly non-Poisson offered traffic. The central purpose of the work is to assess the impact of non-Poisson traffic on routing algorithm developed for Poisson flows. A systematic testing plan for networks with a simple topology and variable levels of capacity, demand and packet length was designed. The results confirmed that Poisson delay formulas together with classical Poisson routing are not appropriate when significant demand is highly variable. The results also show that non-Poisson delay formulas are crucial to the assessment of average delay in these cases.

A rapid and sensitive method for measuring carboxypeptidase N (CPN) activity in human plasma is described. The procedure is based on the hydrolysis of a high-specificity/low-affinity substrate, hippuryl-L-lysine, to its products hippuric acid and lysine. The substrate and product are separated quantitatively by high-performance liquid chromatography in less than 10 min following a minimal sample preparation time. The advantages of this method over previous ones are discussed and data are presented demonstrating the reliability of this method for the routine clinical determination of CPN activity.

The binding interaction of bone Gla protein (BGP), or osteocalcin, to phospholipid vesicles in the presence of calcium has been investigated. Two separate indirect methodologies involving displacement of pyrene-modified Factor Va bound to phospholipid vesicles, and competition with several coagulation proteins in a prothrombin activation assay were performed. Titration of BGP into a cuvette containing phospholipid vesicles (75:25, L-α-phosphatidylcholine/L-α-phosphatidylserine (PCPS] saturated with pyrene-modified Factor Va resulted in a systematic decrease in steady-state anisotropy, suggesting competition for membrane binding sites with pyrene-modified Factor Va. BGP was also found to inhibit thrombin generation in the prothrombin activation assay. Approximately 50% inhibition was observed at 3 µMBGP under phospholipid-limiting (0.5 µMPCPS) concentrations. No inhibition was observed under phospholipid excess (30 µMPCPS) concentrations. Direct measurement of phospholipid binding was measured using equilibrium gel filtration. Elution profiles using fixed lipid (3.4 μmol of PCPS) and varying BGP concentrations (1–17 µM) in the presence of 3 mMCaCl2showed a BGP-phospholipid association. Quantitation of determined isotherm yielded a dissociation constant of 6 ± 1 µMwith a stoichiometry of 102 ± 9 BGP molecules/vesicle at saturation (35 PCPS lipids/BGP) in the presence of 3 mMCaCl2. These results support the hypothesis that protein γ-carboxylation events are coincident with membrane binding potential.