the aim of a multi-mode resource-constrained project scheduling problem (mrcpsp) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). these goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategi...

The problem of efficiently scheduling production jobs on several machines is an important consideration when attempting to make effective use of a multimachines system such as a flexible job shop scheduling production system (FJSP). In most of its practical formulations, the FJSP is known to be NP-hard [8][9], so exact solution methods are unfeasible for most problem instances and heuristic app...

The vehicle routing problem with simultaneous pickup and delivery (VRPSPD) is a well-known combinatorial optimization problem which addresses provided service to a set of customers using a homogeneous fleet of capacitated vehicles. The objective is to minimize the distance traveled. The VRPSPD is an NP-hard combinatorial optimization problem. Therefore, practical large-scale instances of VRPSPD...

Software engineers are frequently faced with tasks that can be expressed as optimization problems. To support them with automation, search-based model-driven engineering combines the abstraction power of models with the versatility of meta-heuristic search algorithms. While current approaches in this area use genetic algorithms with xed mutation operators to explore the solution space, the e ci...

In this paper we propose some non-greedy heuristics and develop an Augmented-Neural-Network (AugNN) formulation for solving the classical open-shop scheduling problem (OSSP). AugNN is a neural network based meta-heuristic approach that allows integration of domain-specific knowledge. The OSSP is framed as a neural network with multiple layers of jobs and machines. Input, output and activation f...

A hybrid meta-heuristic optimization method is introduced to efficiently find the optimal shape of concrete gravity dams including dam-water-foundation rock interaction subjected to earthquake loading. The hybrid meta-heuristic optimization method is based on a hybrid of gravitational search algorithm (GSA) and particle swarm optimization (PSO), which is called GSA-PSO. The operation of GSA-PSO...

Now-a-days different meta-heuristic approaches, their variants and hybrids are being applied for solving Combinatorial Optimization Problems (COP). In this paper Resource Constrained Project Scheduling Problem (RCPSP) has been presented as a COP. This is a common problem for many construction projects. It is highly constrained and is categorized as a NP-hard problem. In our earlier work Simulat...

-In this paper a Meta-heuristic approach for solving the N-Queens Problem is introduced to find the best possible solution in a reasonable amount of time. Genetic Algorithm is used with a novel fitness function as the Meta-heuristic. The aim of N-Queens Problem is to place N queens on an N x N chessboard, in a way so that no queen is in conflict with the others. Chromosome representation and ge...