Discrete-continuous project scheduling problems with positive discounted cash flows andthe maximization of the NPV are considered. We deal with a class of theseproblems with an arbitrary number of discrete resources and one continuous, renewableresource. Activities are nonpreemptable, and the processing rate of an activity is acontinuous, increasing function of the amount of the continuous resource allotted to theactivity at a time. Three common payment models – Lump Sum Payment, Payments at ActivityCompletion times, and payments in Equal Time Intervals are analyzed. Formulations ofmathematical programming problems for an optimal continuous resource allocation for eachpayment model are presented. Applications of two local search metaheuristics – Tabu Searchand Simulated Annealing are proposed. The algorithms are compared on a basis ofcomputational experiments. Some conclusions and directions for future research are pointedout.

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.

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

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

In this paper, we develop the concept of almost stochastic dominance for higher orderpreferences and investigate the related properties of this concept.

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

Data envelopment analysis (DEA) has been widely used to measure the performance of theoperational units that convert multiple inputs into multiple outputs. In many real worldscenarios, there are systems that have a two-stage network process with shared inputs usedin both stages of productions. In this paper, the problem of evaluating the efficiency ofa 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 connectedserially with the process in the second stage. The paper develops a DEA approach formeasuring efficiency of decision processes which can be divided into two stages. Thisapplication of parallel-series production process involves shared resources and the paperdetermines an optimal split of shared resources among two components.

In general, traditional production-inventory systems are based on a number of simplifying– but somewhat unrealistic – assumptions, including constant demand rate, constant holdingcost, and instantaneous order replenishment. These assumptions have been individuallychallenged in numerous variations of production-inventory models. Finite production ratemodels, such as economic production quantity (EPQ) systems consider gradual orderreplenishment. Stock-dependent demand models assume the demand rate to be an elasticfunction of the inventory level. Variable holding cost models assume the holding cost perunit per time period to be a function of the time spent in storage. In this paper, thethree simplifying assumptions are simultaneously relaxed in a new production-inventorysystem with a finite production rate, stock-level dependent demand rate, and variableholding cost. Mathematical models and optimum solution procedures, including nonlinearprogramming, are presented for two functional forms of holding cost variability. The maincontribution of this paper is the formulation and solution of a new production-inventorymodel that more closely represents real-world situations. The realistic assumptions andefficient solution algorithms should make the model practical and useful for industrialapplications.