In this paper, we compare three multi-objective algorithms based on Variable Neighborhood Search (VNS) heuristic. The are applied to solve the single machine scheduling problem with sequence dependent setup times and distinct due windows. problem, consider minimizing total weighted earliness/tardiness flowtime criteria. We introduce two intensification procedures improve a VNS (MOVNS) algorithm proposed in literature. performance of is tested set medium larger instances problem....

In this article, we propose a greedy randomized adaptive search procedure (GRASP) to generate good approximation of the efficient or Pareto optimal set multi-objective combinatorial optimization problem. The algorithm is based on all weighted linear utility functions. each iteration, preference vector defined and solution built considering preferences objective. found submitted local trying improve value function. order find variety solutions, use different vectors, which are distributed...

This paper considers an unrelated parallel machine scheduling problem with the objective of minimizing total earliness and tardiness penalties. Machine job-sequence dependent setup times idle are considered. Since studied is NP-Hard, we test applicability algorithms based on Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic to determine near-optimal solutions. We propose three different heuristics. The first a simple GRASP heuristic, second heuristic includes intensification...

This paper presents a hybrid metaheuristic for the single vehicle routing problem with deliveries and selective pickups (SVRPDSP). A departs loaded from depot, visit every customer delivering certain amount of goods according to their demand, optionally pickup items those customers, receiving profit each realized. The has limited capacity, which may turn impossible attend all pickups, or make this unprofitable if it come back later in after unloaded enough fit demand. objective is find...

In this paper the NP-hard problem of scheduling jobs in a single machine with sequence dependent setup times is considered objective minimizing total tardiness respect to due dates. An iterative local search (ILS) heuristic proposed which uses GRASP (greedy randomized adaptive procedure) algorithm generate an initial solution. The ILS compared by Gupta and Smith (2006) ant colony optimization (ACO) Ching Hsiao (2007). These algorithms obtained better solutions than other from literature....

In this paper we address a three-stage assembly flowshop scheduling problem where there are m machines at the first stage, transportation machine second stage and an third stage. At different parts of product manufactured independently on parallel production lines. collected transferred to next assembled into final products. The objective is schedule n jobs so that total flowtime tardiness minimized simultaneously. This has many applications in industry belongs class NP-Hard combinatorial...

This work considers the unrelated parallel machines scheduling problem with family setups and resource constraints. In this problem, jobs are grouped into families setup times required between belonging to different families. The processing of a job requires certain amount from machine, which is supplied by upstream processes. total consumed processed on machine must not exceed supply up. objective schedule so that tardiness minimized. attempting obtain optimal solutions for small size...

This paper addresses a single-machine scheduling problem with sequence-dependent family setup times. In this the jobs are classified into families according to their similarity characteristics. Setup times required on each occasion when machine switches from processing in one another family. The performance measure be minimized is total tardiness respect given due dates of jobs. as<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi mathvariant="script">N</mml:mi><mml:mi...

In wireless sensors networks (WSNs) the efficient use of sensors' energy is a key point to extend network lifetime and has been center attention by many researchers. There are several different techniques reduce sensor's consumption. Sensor node clustering one these techniques. However, finding an optimal in WSNs NP-Hard problem, thus heuristics needed find good reasonable time. this work we propose analyze Greedy Randomized Adaptative Search Procedure (GRASP) coupled with Path Relinking...

This paper describes a successful combination of genetic algorithm and local search procedure to find good solutions for just-in-time job-shop scheduling problem with earliness tardiness penalties. For each job is given specific order machines in which its operations must be processed, operation has due date, processing time, penalties, are paid if the completed before or after date. The very hard solve optimality even small instances, but proposed found some improving performance when...

This paper considers the Flow shop Sequence Dependent Group Scheduling (FSDGS) problem with minimization of total flow time criterion. In this problem, n jobs to be processed on m machines are grouped in families (groups) a way that machine setup is needed between two consecutive different groups. The FSDGS classified as NP-hard, thus, efficient heuristics obtain near-optimal solutions reasonable computational time. work, we propose an Iterated Local Search (ILS) heuristic. Our heuristic...

This study considers a single machine scheduling problem with the objective of minimizing total weighted tardiness jobs. is one most famous problems in theory and it NP-hard. In this paper, we propose hybrid heuristic which combines GRASP Path Relinking to find good quality solutions for considered problem. The performance tested over multiple benchmark from OR-Library up 100 jobs experimental results show that very competitive existing performing algorithms.