One main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. This paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. Indeed, the nature of products is considered different and hub capacity constraint is also applied. Due to ...

The aim of this paper is to investigate and optimize surface quality and geometrical characteristics in drilling process of AISI H13 steel, because they are critical items for precision manufacturing. After conducting the experiments, two regression models are developed to extensively evaluate the effect of drilling parameters on process outputs. After that, evolutionary multi-objective optimiz...

This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimization tool for solving this problem. The proposed methodology is based on a new variant of ant colony optimization (ACO) specialized in multi-objective o...

A novel multiobjective optimisation accelerator is introduced that uses direct manipulation in objective space together with neural network mappings from objective space to decision space. This operator is a portable component that can be hybridized with any multiobjective optimisation algorithm. The purpose of this Convergence Acceleration Operator (CAO) is to enhance the search capability and...

To solve single and multi-objective optimization problems, evolutionary algorithms have been created. We use the non-dominated sorting genetic algorithm (NSGA-II) to find Pareto front in a two-objective portfolio query, its extended variant NSGA-III three-objective problem, this article. Furthermore, both we quantify Karush-Kuhn-Tucker Proximity Measure (KKTPM) for each generation determine how...

A guided stochastic search algorithm, known as the repeated weighted boosting search (RWBS), offers an effective means for solving the difficult single-objective optimisation problems with non-smooth and/or multi-modal cost functions. Compared with other global optimisation solvers, such as the genetic algorithms (GAs) and adaptive simulated annealing, RWBS is easier to implement, has fewer alg...

Low specific speed centrifugal pumps (LSSCP) are widely utilized in district energy systems to promote the integration of renewable energy. However, performance LSSCP becomes inefficient due harsh operating conditions resulting substantial increase consumption. Many-objective optimization is significant improving and promoting sustainability systems. Among existing methods, global methods limit...

The binaphthol enantiomers separation process using simulation moving bed technology is simulated with the true moving bed approach (TMB). In order to systematically optimize the process with multiple productive objectives, this article develops a variant of tissue P system (TPS). Inspired by general tissue P systems, the special TPS has a tissue-like structure with several membranes. The key r...