Showing papers in "Rairo-operations Research in 2014"

Fuzzy Mathematical Programming approach for Solving Fuzzy Linear Fractional Programming Problem

Abstract: In this paper, a solution procedure is proposed to solve fuzzy linear fractional programming (FLFP) problem where cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. Here, the FLFP problem is transformed into an equivalent deterministic multi-objective linear fractional programming (MOLFP) problem. By using Fuzzy Mathematical programming approach transformed MOLFP problem is reduced single objective linear programming (LP) problem. The proposed procedure illustrated through a numerical example.

Managing a patient waiting list with time-dependent priority and adverse events

Abstract: This paper addresses the problem of managing a waiting list for elective surgery to decide the number of patients selected from the waiting list and to schedule them in accordance with the operating room capacity in the next period. The waiting list prioritizes patients not only by their initial urgency level but also by their waiting time. Selecting elective surgery patients requires a balance between the waiting time for urgent patients and that for less urgent patients. The problem is formulated as an infinite horizon Markov Decision Process. Further, the study proposes a scheduling procedure based on structural properties of an optimal policy by taking a sampling-based finite horizon approximation approach. Finally, we examine the performance of the policy under various conditions.

The Orderly Colored Longest Path Problem – a survey of applications and new algorithms

Abstract: A concept of an Orderly Colored Longest Path (OCLP) refers to the problem of finding the longest path in a graph whose edges are colored with a given number of colors, under the constraint that the path follows a predefined order of colors. The problem has not been widely studied in the previous literature, especially for more than two colors in the color arrangement sequence. The recent and relevant application of OCLP is related to the interpretation of Nuclear Magnetic Resonance experiments for RNA molecules. Besides, an employment of this specific graph model can be found in transportation, games, and grid graphs. OCLP models the relationships between consecutive edges of the path, thus it appears very useful in representing the real problems with specific ties between their components. In the paper, we show OCLP’s correlation with similar issues known in graph theory. We describe the applications, three alternative models and new integer programming algorithms to solve OCLP. They are formulated by means of max flow problems in a directed graph with packing constraints over certain partitions of nodes. The methods are compared in a computational experiment run for a set of randomly generated instances.

Simulated annealing and tabu search for discrete-continuous project scheduling with discounted cash flows

Abstract: Discrete-continuous project scheduling problems with positive discounted cash flows and the maximization of the NPV are considered. We deal with a class of these problems with an arbitrary number of discrete resources and one continuous, renewable resource. Activities are nonpreemptable, and the processing rate of an activity is a continuous, increasing function of the amount of the continuous resource allotted to the activity at a time. Three common payment models – Lump Sum Payment, Payments at Activity Completion times, and payments in Equal Time Intervals are analyzed. Formulations of mathematical programming problems for an optimal continuous resource allocation for each payment model are presented. Applications of two local search metaheuristics – Tabu Search and Simulated Annealing are proposed. The algorithms are compared on a basis of computational experiments. Some conclusions and directions for future research are pointed out.

Block decomposition approach to compute a minimum geodetic set

Abstract: In this paper, we develop a divide-and-conquer approach, called block decomposition, to solve the minimum geodetic set problem. This provides us with a unified approach for all graphs admitting blocks for which the problem of finding a minimum geodetic set containing a given set of vertices (g -extension problem) can be efficiently solved. Our method allows us to derive linear time algorithms for the minimum geodetic set problem in (a proper superclass of) block-cacti and monopolar chordal graphs. Also, we show that hull sets and geodetic sets of block-cacti are the same, and the minimum geodetic set problem is NP-hard in cobipartite graphs. We conclude by pointing out several interesting research directions.

The MX/M/1 queue with working breakdown

Abstract: In this paper, we consider a batch arrival MX/M/1 queue model with working breakdown. The server may be subject to a service breakdown when it is busy, rather than completely stoping service, it will decrease its service rate. For this model, we analyze a two-dimensional Markov chain and give its quasi upper triangle transition probability matrix. Under the system stability condition, we derive the probability generating function (PGF) of the stationary queue length, and then obtain its stochastic decomposition, which shows the relationship with that of the classical MX/M/ 1 queue without vacation or breakdown. Besides, we also give the Laplace-Stieltjes transform (LST) of the stationary waiting time distribution of an arbitrary customer in a batch. Finally, some numerical examples are given to illustrate the effect of the parameters on the system performance measures.

Solving multi-agent scheduling problems on parallel machines with a global objective function

Abstract: In this study, we consider a scheduling environment with m ( m ≥ 1) parallel machines. The set of jobs to schedule is divided into K disjoint subsets. Each subset of jobs is associated with one agent. The K agents compete to perform their jobs on common resources. The objective is to find a schedule that minimizes a global objective function f 0 , while maintaining the regular objective function of each agent, f k , at a level no greater than a fixed value, e k ( f k ∈ { f k max , ∑ f k }, k = 0, ..., K ). This problem is a multi-agent scheduling problem with a global objective function . In this study, we consider the case with preemption and the case without preemption. If preemption is allowed, we propose a polynomial time algorithm based on a network flow approach for the unrelated parallel machine case. If preemption is not allowed, we propose some general complexity results and develop dynamic programming algorithms.

Reconfigurable Dynamic Cellular Manufacturing System: A New Bi-Objective Mathematical Model

Abstract: Dynamic Cell Formation Problem (DCFP) seeks to cope with variation in part mix and demands using machine relocation, replication, and removing; whilst from practical point of view it is too hard to move machines between cells or invest on machine replication. To cope with this deficiency, this paper addresses Reconfigurable Dynamic Cell Formation Problem (RDCFP) in which machine modification is conducted instead of their relocation or replication in order to enhance machine capabilities to process wider range of production tasks. In this regard, a mixed integer nonlinear mathematical model is proposed, which is NP-hard. To cope with the proposed model’s intractability, an Imperialist Competitive Algorithm (ICA) is developed, whose obtained results are compared with those of Genetic Algorithm’s (GA’s), showing superiority and outperformance of the developed ICA.

Production-inventory system with finite production rate, stock-dependent demand, and variable holding cost

Abstract: In general, traditional production-inventory systems are based on a number of simplifying – but somewhat unrealistic – assumptions, including constant demand rate, constant holding cost, and instantaneous order replenishment. These assumptions have been individually challenged in numerous variations of production-inventory models. Finite production rate models, such as economic production quantity (EPQ) systems consider gradual order replenishment. Stock-dependent demand models assume the demand rate to be an elastic function of the inventory level. Variable holding cost models assume the holding cost per unit per time period to be a function of the time spent in storage. In this paper, the three simplifying assumptions are simultaneously relaxed in a new production-inventory system with a finite production rate, stock-level dependent demand rate, and variable holding cost. Mathematical models and optimum solution procedures, including nonlinear programming, are presented for two functional forms of holding cost variability. The main contribution of this paper is the formulation and solution of a new production-inventory model that more closely represents real-world situations. The realistic assumptions and efficient solution algorithms should make the model practical and useful for industrial applications.

Two-stage robust optimization, state-space representable uncertainty and applications

Abstract: The present paper addresses the class of two-stage robust optimization problems which can be formulated as mathematical programs with uncertainty on the right-hand side coefficients (RHS uncertainty). The wide variety of applications and the fact that many problems in the class have been shown to be NP-hard, motivates the search for efficiently solvable special cases. Accordingly, the first objective of the paper is to provide an overview of the most important applications and of various polynomial or pseudo-polynomial special cases identified so far. The second objective is to introduce a new subclass of polynomially solvable robust optimization problems with RHS uncertainty based on the concept of state-space representable uncertainty sets . A typical application to a multi period energy production problem under uncertain customer load requirements is described into details, and computational results including a comparison between optimal two-stage solutions and exact optimal multistage strategies are discussed.

A branch and bound algorithm for the two-machine flowshop problem with unit-time operations and time delays

Abstract: In this paper we consider the problem of scheduling, on a two-machine flowshop, a set of unit-time operations subject to time delays with respect to the makespan. This problem is known to be \hbox{${\cal NP}$}-hard in the strong sense. We propose an algorithm based on a branch and bound enumeration scheme. This algorithm includes the implementation of new lower and upper bound procedures, and dominance rules. A computer simulation to measure the performance of the algorithm is provided for a wide range of test problems.

Multi-objective geometric programming problem with Karush−Kuhn−Tucker condition using ϵ-constraint method

Abstract: Optimization is an important tool widely used in formulation of the mathematical model and design of various decision making problems related to the science and engineering. Generally, the real world problems are occurring in the form of multi-criteria and multi-choice with certain constraints. There is no such single optimal solution exist which could optimize all the objective functions simultaneously. In this paper, ϵ -constraint method along with Karush−Kuhn−Tucker (KKT) condition has been used to solve multi-objective Geometric programming problems(MOGPP) for searching a compromise solution. To find the suitable compromise solution for multi-objective Geometric programming problems, a brief solution procedure using ϵ -constraint method has been presented. The basic concept and classical principle of multi-objective optimization problems with KKT condition has been discussed. The result obtained by ϵ -constraint method with help of KKT condition has been compared with the result so obtained by Fuzzy programming method. Illustrative examples are presented to demonstrate the correctness of proposed model.

A note on robust Nash equilibria with uncertainties

Abstract: In this short note, we investigate the framework where agents or players have some uncertainties upon their payoffs or losses, the behavior (or the type, number or any other characteristics) of other players. More specifically, we introduce an extension of the concept of Nash equilibria that generalize different solution concepts called by their authors, and depending on the context, either as robust, ambiguous, partially specified or with uncertainty aversion. We provide a simple necessary and sufficient condition that guarantees its existence and we show that it is actually a selection of conjectural (or self-confirming) equilibria. We finally conclude by how this concept can and should be defined in games with partial monitoring in order to preserve existence properties.

Estimating the supply chain efficiency loss when the seller has to estimate the buyer's willingness to pay

Abstract: We study the pricing problem between two firms when the manufacturer’s willingness to pay (wtp) for the supplier’s good is not known by the latter. We demonstrate that it is in the interest of the manufacturer to hide this information from the supplier. The precision of the information available to the supplier modifies the rent distribution. The risk of opportunistic behaviour entails a loss of efficiency in the supply chain. The model is extended to the case of a supplier submitting offers to several manufacturers. Some managerial insight through a numerical illustration is provided.

Wage bargaining with discount rates varying in time under different strike decisions

Abstract: We present a non-cooperative union-firm wage bargaining model in which the union must choose between strike and holdout if a proposed wage contract is rejected. The innovative element that our model brings to the existing literature on wage bargaining, concerns the parties' preferences which are not expressed by constant discount rates, but by sequences of discount factors varying in time. First, we determine subgame perfect equilibria if the strike decision of the union is exogenous. We analyze the case when the union is committed to strike in each disagreement period, the case when the union is committed to strike only when its own offer is rejected, and the case of the never strike exogenous decision. A comparison of the results is provided, among the cases of the exogenous strike decisions. Next, we consider the general model with no assumption on the commitment to strike. We find subgame perfect equilibria in which the strategies supporting the equilibria in the exogenous cases are combined with the minimum-wage strategies, provided that the firm is not less patient than the union. If the firm is more impatient than the union, then the firm is better off by playing the no-concession strategy. We find a subgame perfect equilibrium for this case.

A DEA model for two-stage parallel-series production processes

Abstract: Data envelopment analysis (DEA) has been widely used to measure the performance of the operational units that convert multiple inputs into multiple outputs. In many real world scenarios, there are systems that have a two-stage network process with shared inputs used in both stages of productions. In this paper, the problem of evaluating the efficiency of a set of specialized and interdependent components that make up a large DMU is considered. In these processes the first stage consists of two parallel components which are connected serially with the process in the second stage. The paper develops a DEA approach for measuring efficiency of decision processes which can be divided into two stages. This application of parallel-series production process involves shared resources and the paper determines an optimal split of shared resources among two components.

Multi-objective Optimization Problem with Bounded Parameters

Abstract: In this paper, we propose a nonlinear multi-objective optimization problem whose parameters in the objective functions and constraints vary in between some lower and upper bounds. Existence of the efficient solution of this model is studied and gradient based as well as gradient free optimality conditions are derived. The theoretical developments are illustrated through numerical examples.

A polyhedral study of a two level facility location model

Abstract: We study an uncapacitated facility location model where customers are served by facilities of level one, then each level one facility that is opened must be assigned to an opened facility of level two. We identify a polynomially solvable case, and study some valid inequalities and facets of the associated polytope.

Performance analysis of single server non-Markovian retrial queue with working vacation and constant retrial policy

Abstract: This paper analyses an M/G/1 retrial queue with working vacation and constant retrial policy. As soon as the system becomes empty, the server begins a working vacation. The server works with different service rates rather than completely stopping service during a vacation. We construct the mathematical model and derive the steady-state queue distribution of number of customer in the retrial group. The effects of various performance measures are derived.

Finite buffer GI/Geo/ 1 batch servicing queue with multiple working vacations

Abstract: This paper analyzes a discrete-time finite buffer renewal input queue with multiple working vacations where services are performed in batches of maximum size “b ”. The service times both during a regular service period and vacation period and vacation times are geometrically distributed. Employing the supplementary variable and imbedded Markov chain techniques, we derive the steady-state queue length distributions at pre-arrival, arbitrary and outside observer’s observation epochs. Based on the queue length distributions, some performance measures and waiting time distribution in the queue have been discussed. Finally, numerical results showing the effect of model parameters on the key performance measures are presented.

An improved ant algorithm for Multi-mode Resource Constrained Project Scheduling Problem

Abstract: Many real-world scheduling problems can be modeled as Multi-mode Resource Constrained Project Scheduling Problems (MRCPSP). However, the MRCPSP is a strong NP-hard problem and very difficult to be solved. The purpose of this research is to investigate a more efficient alternative based on ant algorithm to solve MRCPSP. To enhance the generality along with efficiency of the algorithm, the rule pool is designed to manage numerous priority rules for MRCPSP. Each ant is provided with an independent thread and endowed with the learning ability to dynamically select the excellent priority rules. In addition, all the ants in the ant algorithm have the prejudgment ability to avoid infeasible routes based on the branch and bound method. The algorithm is tested on the well-known benchmark instances in PSPLIB. The computational results validate the effectiveness of the proposed algorithm.

Unified duality for vector optimization problem over cones involving support functions

Abstract: In this paper we give necessary and sufficient optimality conditions for a vector optimization problem over cones involving support functions in objective as well as constraints, using cone-convex and other related functions. We also associate a unified dual to the primal problem and establish weak, strong and converse duality results. A number of previously studied problems appear as special cases.

A Branch-and-Cut for the non-disjoint m-Ring-Star problem

Abstract: In this article we study the realistic network topology of Synchronous Digital Hierarchy (SDH) networks. We describe how providers fulfill customer connectivity requirements. We show that SDH Network design reduces to the Non-Disjoint m-Ring-Star Problem (NDRSP). We first show that there is no two-index integer formulation for this problem. We then present a natural 3-index formulation for the NDRSP together with some classes of valid inequalities that are used as cutting planes in a Branch-and-Cut approach. We propose a polyhedral study of a polytope associated with this formulation. Finally, we present our Branch-and-Cut algorithm and give some experimental results on both random and real instances.

Complementarities and the existence of strong Berge equilibrium

Abstract: This paper studies the existence and the order structure of strong Berge equilibrium, a refinement of Nash equilibrium, for games with strategic complementarities a la strong Berge . It is shown that the equilibrium set is a nonempty complete lattice. Moreover, we provide a monotone comparative statics result such that the greatest and the lowest equilibria are increasing.

Fuzzy Linear Fractional Set Covering Problem with Imprecise Costs

Abstract: Set covering problems are in great use these days, these problems are applied in many disciplines such as crew scheduling problems, location problems, testing of VLSI circuits, artificial intelligence etc . In this paper α -acceptable optimal solution is given for the fuzzy linear fractional set covering problem where fuzziness involved in the objective function. At first the fuzzy linear fractional problem is being converted in to crisp parametric linear fractional set covering problem then a linearization technique is used to obtain an optimal solution to this parametric problem. This optimal solution will also be the fuzzy optimal solution for the original problem. An example is also provided to illustrate the algorithm.

Almost Higher Order Stochastic Dominance

Abstract: In this paper, we develop the concept of almost stochastic dominance for higher order preferences and investigate the related properties of this concept.

Fluid limits for the queue length of jobs in multiserver open queueing networks

Abstract: The object of this research in the queueing theory is a theorem about the Strong-Law-of-Large-Numbers (SLLN) under the conditions of heavy traffic in a multiserver open queueing network. SLLN is known as a fluid limit or fluid approximation. In this work, we prove that the long-term average rate of growth of the queue length process of a multiserver open queueing network under heavy traffic strongly converges to a particular vector of rates. SLLN is proved for the values of an important probabilistic characteristic of the multiserver open queueing network investigated as well as the queue length of jobs.

Integer programming approaches for minimum stabbing problems

Abstract: The problem of finding structures with minimum stabbing number has received considerable attention from researchers. Particularly, [10] study the minimum stabbing number of perfect matchings (mspm), spanning trees (msst) and triangulations (mstr) associated to set of points in the plane. The complexity of the mstr remains open whilst the other two are known to be 𝓝𝓟-hard. This paper presents integer programming (ip) formulations for these three problems, that allowed us to solve them to optimality through ip branch-and-bound (b&b) or branch-and-cut (b&c) algorithms. Moreover, these models are the basis for the development of Lagrangian heuristics. Computational tests were conducted with instances taken from the literature where the performance of the Lagrangian heuristics were compared with that of the exact b&b and b&c algorithms. The results reveal that the Lagrangian heuristics yield solutions with minute, and often null, duality gaps for instances with several hundreds of points in small computation times. To our knowledge, this is the first computational study ever reported in which these three stabbing problems are considered and where provably optimal solutions are given.

Process parameter prediction via markov models of sub-activities

Abstract: This work aims to fill a lacunae in the project-oriented production systems literature providing a formal analytic description of the rework effects formulae and the determination of the extended design time due to a certain degree of overlapping in a pair of activities. It is made through the utilization of concepts of workflow construction with hidden (semi) Markov models theory and establishing a way to disaggregate activities into sub-activities, in order to determine the activity parameters used by the project scheduling techniques. With the aim to make a correlation between the entropy of the state transitions and the probability of changes, the information theory is also used, and the concept of impact caused by the probability of changes is provided. Numerical examples are shown for the purpose to demonstrate the applicability of the concepts developed, and one example of overlapping of two activities is shown. The original contributions of this work are shown on the last section.

A distributed transportation simplex applied to a Content Distribution Network problem

Abstract: A Content Distribution Network (CDN) can be defined as an overlay system that replicates copies of contents at multiple points of a network, close to the final users, with the objective of improving data access. CDN technology is widely used for the distribution of large-sized contents, like in video streaming. In this paper we address the problem of finding the best server for each customer request in CDNs, in order to minimize the overall cost. We consider the problem as a transportation problem and a distributed algorithm is proposed to solve it. The algorithm is composed of two independent phases: a distributed heuristic finds an initial solution that may be later improved by a distributed transportation simplex algorithm. It is compared with the sequential version of the transportation simplex and with an auction-based distributed algorithm. Computational experiments carried out on a set of instances adapted from the literature revealed that our distributed approach has a performance similar or better to its sequential counterpart, in spite of not requiring global information about the contents requests. Moreover, the results also showed that the new method outperforms the based-auction distributed algorithm.