In this paper, a preemptive multi-objective multi-mode project scheduling model for resource investment problem is proposed. The first objective function is to minimize the completion time of project (makespan);the second objective function is to minimize the cost of using renewable resources. Non-renewable resources are also considered as parameters in this model. The preemption of activities ...

Local Genetic Algorithms are search procedures designed in order to provide an effective local search. Several Genetic Algorithm models have recently been presented with this aim. In this paper we present a new Binary-coded Local Genetic Algorithm based on a Steady-State Genetic Algorithm with a crowding replacement method. We have compared a Multi-Start Local Search based on the Binary-Coded L...

The permutation flow shop scheduling problem (PFSP) is one of the most well known and well studied production scheduling problems with strong industrial background. Most scheduling problems are combinatorial optimization problems which are too difficult to be solved optimally, and hence heuristics are used to obtain good solutions in a reasonable time. The specific goal of this paper is to inve...

This paper presents an application of a hierarchical social (HS) metaheuristic to region-based segmentation. The original image is modelled as a simplified image graph, which is successively partitioned into two regions, corresponding to the most significant components of the actual image, until a termination condition is met. The graph-partitioning task is solved as a variant of the min-cut pr...

this paper studies the multi-stage supply chain system (msscm) controlled by the kanban mechanism. in the kanban system, decision making is based on the number of kanbans as well as batch sizes. a kanban mechanism is employed to assist in linking different production processes in a supply chain system in order to implement the scope of just-in-time (jit) philosophy. for a msscm, a mixed-integer...

We proposed a population-based metaheuristic called the spy algorithm for solving optimization problems and evaluated its performance. The design of our ensures benefit exploration exploitation as well cooperative non-cooperative searches in each iteration. compared with genetic algorithm, improved harmony search, particle swarm on set non-convex functions that focus accuracy, ability detecting...

Assortment planning is the process in which a retailer selects a product line to offer to customers and is a key determinant of a retailer’s profit. We consider the assortment planning problem using a locational choice model for customer product selection and allow for both horizontal and vertical product differentiation. When the distribution of customer preference is unimodal, the optimal sol...

In this paper, we propose three new metaheuristic implementations to address the problem of minimizing the makespan in a hybrid flexible flowshop with sequence-dependent setup times. The first metaheuristic is a genetic algorithm (GA) embedding two new crossover operators, and the second is an ant colony optimization (ACO) algorithm which incorporates a transition rule featuring lookahead infor...

Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers t...