6,017 research outputs found
Cooperation between Branch and Bound and Evolutionary Approaches to Solve a Bi-objective Flow Shop Problem
Over the years, many techniques have been established to solve NP-Hard Optimization Problems and in particular multiobjective problems. Each of them are efficient on several types of problems or instances. We can distinguish exact methods dedicated to solve small instances, from heuristics – and particularly metaheuristics – that approximate best solutions on large instances. In this article, we firstly present an efficient exact method, called the two-phases method. We apply it to a biobjective Flow Shop Problem to find the optimal set of solutions. Exact methods are limited by the size of the instances, so we propose an original cooperation between this exact method and a Genetic Algorithm to obtain good results on large instances. Results obtained are promising and show that cooperation between antagonist optimization methods could be very efficient
Bütünleşik tedarik zinciri çizelgeleme modelleri: Bir literatür taraması
Research on integration of supply chain and scheduling is relatively recent, and
number of studies on this topic is increasing. This study provides a comprehensive
literature survey about Integrated Supply Chain Scheduling (ISCS) models to help
identify deficiencies in this area. For this purpose, it is thought that this study will
contribute in terms of guiding researchers working in this field. In this study,
existing literature on ISCS problems are reviewed and summarized by introducing
the new classification scheme. The studies were categorized by considering the
features such as the number of customers (single or multiple), product lifespan
(limited or unlimited), order sizes (equal or general), vehicle characteristics
(limited/sufficient and homogeneous/heterogeneous), machine configurations and
number of objective function (single or multi objective). In addition, properties of
mathematical models applied for problems and solution approaches are also
discussed.Bütünleşik Tedarik Zinciri Çizelgeleme (BTZÇ) üzerine yapılan araştırmalar
nispeten yenidir ve bu konu üzerine yapılan çalışma sayısı artmaktadır. Bu çalışma,
bu alandaki eksiklikleri tespit etmeye yardımcı olmak için BTZÇ modelleri hakkında
kapsamlı bir literatür araştırması sunmaktadır. Bu amaçla, bu çalışmanın bu alanda
çalışan araştırmacılara rehberlik etmesi açısından katkı sağlayacağı
düşünülmektedir. Bu çalışmada, BTZÇ problemleri üzerine mevcut literatür gözden
geçirilmiş ve yeni sınıflandırma şeması tanıtılarak çalışmalar özetlenmiştir.
Çalışmalar; tek veya çoklu müşteri sayısı, sipariş büyüklüğü tipi (eşit veya genel),
ürün ömrü (sınırlı veya sınırsız), araç karakteristikleri (sınırlı/yeterli ve
homojen/heterojen), makine konfigürasyonları ve amaç fonksiyonu sayısı (tek veya
çok amaçlı) gibi özellikler dikkate alınarak kategorize edildi. Ayrıca problemler için
uygulanan matematiksel modellerin özellikleri ve çözüm yaklaşımları da
tartışılmıştır
A survey of parallel hybrid applications to the permutation flow shop scheduling problem and similar problems
Parallel algorithms have focused an increased interest due to advantages in computation time and quality of solutions when applied to industrial engineering problems. This communication is a survey and classification of works in the field of hybrid algorithms implemented in parallel and applied to combinatorial optimization problems similar to the to the permutation flowshop problem with the objective of minimizing the makespan, Fm|prmu|Cmax according to the Graham notation, the travelling salesman problem (TSP), the quadratic assignment problem (QAP) and, in general, those whose solution can be expressed as a permutation
Exact and Heuristic Algorithms for the Job Shop Scheduling Problem with Earliness and Tardiness Over a Common Due Date
Scheduling has turned out to be a fundamental activity for both production and service organizations. As competitive markets emerge, Just-In-Time (JIT) production has obtained more importance as a way of rapidly responding to continuously changing market forces. Due to their realistic assumptions, job shop production environments have gained much research effort among scheduling researchers. This research develops exact and heuristic methods and algorithms to solve the job shop scheduling problem when the objective is to minimize both earliness and tardiness costs over a common due date. The objective function of minimizing earliness and tardiness costs captures the essence of the JIT approach in job shops. A dynamic programming procedure is developed to solve smaller instances of the problem, and a Multi-Agent Systems approach is developed and implemented to solve the problem for larger instances since this problem is known to be NP-Hard in a strong sense. A combinational auction-based approach using a Mixed-Integer Linear Programming (MILP) model to construct and evaluate the bids is proposed. The results showed that the proposed combinational auction-based algorithm is able to find optimal solutions for problems that are balanced in processing times across machines. A price discrimination process is successfully implemented to deal with unbalanced problems. The exact and heuristic procedures developed in this research are the first steps to create a structured approach to handle this problem and as a result, a set of benchmark problems will be available to the scheduling research community
Metaheuristics and Their Hybridization to Solve the Bi-objective Ring Star Problem: a Comparative Study
This paper presents and experiments approaches to solve a new bi-objective
routing problem called the ring star problem. It consists of locating a simple
cycle through a subset of nodes of a graph while optimizing two kinds of cost.
The first objective is the minimization of a ring cost that is related to the
length of the cycle. The second one is the minimization of an assignment cost
from non-visited nodes to visited ones. In spite of its obvious bi-objective
formulation, this problem has always been investigated in a single-objective
way. To tackle the bi-objective ring star problem, we first investigate
different stand-alone search methods. Then, we propose two cooperative
strategies that combines two multiple objective metaheuristics: an elitist
evolutionary algorithm and a population-based local search. We apply this new
hybrid approaches to well-known benchmark test instances and demonstrate their
effectiveness in comparison to non-hybrid algorithms and to state-of-the-art
methods
A Polyhedral Study of Mixed 0-1 Set
We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set
Multilevel decision-making: A survey
© 2016 Elsevier Inc. All rights reserved. Multilevel decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a multiple level hierarchy. Significant efforts have been devoted to understanding the fundamental concepts and developing diverse solution algorithms associated with multilevel decision-making by researchers in areas of both mathematics/computer science and business areas. Researchers have emphasized the importance of developing a range of multilevel decision-making techniques to handle a wide variety of management and optimization problems in real-world applications, and have successfully gained experience in this area. It is thus vital that a high quality, instructive review of current trends should be conducted, not only of the theoretical research results but also the practical developments in multilevel decision-making in business. This paper systematically reviews up-to-date multilevel decision-making techniques and clusters related technique developments into four main categories: bi-level decision-making (including multi-objective and multi-follower situations), tri-level decision-making, fuzzy multilevel decision-making, and the applications of these techniques in different domains. By providing state-of-the-art knowledge, this survey will directly support researchers and practical professionals in their understanding of developments in theoretical research results and applications in relation to multilevel decision-making techniques
Metaheuristics and cooperative approaches for the Bi-objective Ring Star Problem
International audienceThis paper presents and investigates different approaches to solve a new bi-objective routing problem called the ring star problem. It consists of locating a simple cycle through a subset of nodes of a graph while optimizing two kinds of cost. The first objective is the minimization of a ring cost that is related to the length of the cycle. The second one is the minimization of an assignment cost from non-visited nodes to visited ones. In spite of its obvious bi-objective formulation, this problem has always been investigated in a single-objective way. To tackle the bi-objective ring star problem, we first investigate different stand-alone search methods. Then, we propose two cooperative strategies that combine two multi-objective metaheuristics: an elitist evolutionary algorithm and a population-based local search. We apply these new hybrid approaches to well-known benchmark test instances and demonstrate their effectiveness in comparison to non-hybrid algorithms and to state-of-the-art methods
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