The problem of maximal hub covering as a challenging problem in operation research. Transportation programming seeks to find an optimal location of a set of hubs to reach maximum flow in a network. Since the main structure's parameters of the problem such as origin-destination flows, costs and travel time, change periodically in the real world applications, new issues arise in handling it. In t...

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics (RL) network. The success of a logistics system may depend on the decisions of the facilities locations and vehicle routings. The location-routing problem (LRP) simultaneously locates the facilities and designs the travel routes for vehicles among ...

in the real world, risk and uncertainty are two natural properties in the implementation of mega projects. most projects fail to achieve the pre-determined objectives due to uncertainty. a linear integer programming optimization model was used in this work to solve a problem in order to choose the most appropriate risk responses for the project risks. a mathematical model, in which work structu...

this paper presents a new bi-objective mathematical model for a permutation flowshop scheduling problem with availability constraint in case of preventive maintenance operations on machines. in this paper, preventive maintenance is flexible and there is not a certain time for the maintenance operation; however, time between two consecutive maintenance operations for each machine should not be g...

An algorithm for a constraint satisfaction problem is called robust if it outputs an assignment satisfying at least (1 − g(ε))-fraction of the constraints given a (1 − ε)-satisfiable instance, where g(ε) → 0 as ε → 0. Guruswami and Zhou conjectured a characterization of constraint languages for which the corresponding constraint satisfaction problem admits an efficient robust algorithm. This pa...

Using second-generation biomass and biofuel deal with environmental pollution and CO2 emissions. Therefore, this paper design an integrated multi-period bi-objective biofuel supply chain network using support vector machine (SVM) and economic analysis to reduce the cost of generating biofuels and CO2 emissions. The economic analysis consists of three scenarios for supplyin...

An instance of the Constraint Satisfaction Problem (CSP) is given by a family of constraints on overlapping sets of variables, and the goal is to assign values from a fixed domain to the variables so that all constraints are satisfied. In the optimization version, the goal is to maximize the number of satisfied constraints. An approximation algorithm for CSP is called robust if it outputs an as...

A temporal constraint language Γ is a set of relations with first-order definitions in (Q;<). Let CSP(Γ) denote the set of constraint satisfaction problem instances with relations from Γ. CSP(Γ) admits robust approximation if, for any ε ≥ 0, given a (1 − ε)-satisfiable instance of CSP(Γ), we can compute an assignment that satisfies at least a (1−f(ε))-fraction of constraints in polynomial time....