Showing papers in "Computers & Operations Research in 2017"

TL;DR: A novel classification framework is proposed that provides a full picture of current literature on where and how BDA has been applied within the SCM context and reveals a number of research gaps, which leads to future research directions.

TL;DR: A framework to classify different types of non-emergency and emergency HCFs in terms of location management is presented, and the literature based on the framework is reviewed and future research possibilities are analyzed.

TL;DR: A comprehensive overview of current work in the field of HHC routing and scheduling with a focus on considered problem settings is given and single-period and multi-period problems are differentiated.

TL;DR: Against most existing methods for 3D path following, the proposed robust fuzzy control scheme reduces the design and implementation costs of complicated dynamics controller, and relaxes the knowledge of the accuracy dynamics modelling and environmental disturbances.

TL;DR: This research provides a decision-making tool to solve a multi-period green supplier selection and order allocation problem and provides top management with flexibility in giving more or less importance weight to green or traditional criteria regardless of the number of criteria in each category through the use of AHP, which reduces the effect of thenumber of criteria on the preference weight of the suppliers.

TL;DR: This review introduces the concept of emergency care pathway following the current trend in health care systems, i.e., shifting the central role from health care providers to patients.

TL;DR: A new real-time routing problem, in which different types of drones can collect and deliver packages, and seven different objective functions are considered and sought to be minimized using a Mixed-Integer Linear Programming (MILP) model solved by a matheuristic algorithm.

TL;DR: A number of algorithmic improvements implemented in the AGLIBRARY optimization solver are presented in order to improve the possibility of finding good quality solutions quickly and often outperform a state-of-the-art tabu search algorithm and a commercial solver in terms of reduced computation times and/or train delays.

TL;DR: The production planning problem in additive manufacturing and 3D printing is introduced for the first time in the literature and a mathematical model to formulate it is developed and coded in CPLEX and two different heuristic procedures, namely best-fit and adapted best- fit rules, are developed in JavaScript.

TL;DR: An NDEA model for calculating optimistic and pessimistic efficiency is developed and can incorporate undesirable outputs, and can rank supply chains in terms of efficiency scores.

TL;DR: A metaheuristic, called adaptive large neighborhood search (ALNS), is developed, thus creating a conflict-free observational timeline, and time slacks are introduced to confine the propagation of the time-dependent constraint of transition time.

TL;DR: A single-machine scheduling problem with power-down mechanism to minimize both total energy consumption and maximum tardiness and a basic e − constraint method is proposed to obtain the complete Pareto front of the problem.

TL;DR: It is shown that large sized problems possessing essential 3V's of big data, i.e., volume, variety and velocity consume non-polynomial time and cannot be solved optimally, so a heuristic (H-1) is also proposed to solve the largesized problems involving big data.

TL;DR: In this paper, an iterated local search (ILS) based heuristic is proposed to solve the static bike rebalancing problem, where only a single vehicle is available and the objective is to find a least-cost route that meets the demand of all stations and does not violate the minimum (zero) and maximum (vehicle capacity) load limits along the tour.

TL;DR: This paper presents an effective algorithm for the GTSP based on adaptive large neighborhood search that operates by repeatedly removing from, and inserting vertices in, the tour and proposes a general insertion mechanism that contains as special cases the well-known nearest, farthest and random insertion mechanisms.

TL;DR: This research has sought to provide policymakers with a means to evaluate new and existing policies, whilst also offering a practical basis through which food chains can be made more resilient through the consideration of management practices and policy decisions.

TL;DR: This paper presents iterated greedy algorithms for solving the blocking flowshop scheduling problem (BFSP) with the makespan criterion with a constructive heuristic to generate an initial solution and proposes an iteration jumping probability to employ the swap neighborhood structure.

TL;DR: An Adaptive Large Neighborhood Search (ALNS) algorithm is developed, which can simultaneously handle the network design and line planning problems considering also rolling stock and personnel planning aspects, and is compared with state-of-the-art commercial solvers on a small-size artificial instance.

TL;DR: A multi-objective integer linear programming model aiming at efficiently planning and managing hospital operating room suites and could represent a suitable engine for the development of advanced and effective health care management decision support systems.

TL;DR: A matheuristic based method based on large neighborhood search search and periodically solving a set partitioning and matching problem with third-party solvers for the vehicle routing problem with cross-docking is proposed.

TL;DR: This study was partially supported by Korea National Research Foundation through Global Research Network Program (Project no. 2016S1A2A2912265) and an EU Marie Sklodowska-Curie action funded project, MINI-CHIP.

TL;DR: The possibility of re-optimizing partial solutions obtained after the solution destruction step of the iterated greedy algorithm is explored and it is shown that with this extension, the performance of the state-of-the-art algorithm for the PFSP under makespan criterion can be significantly improved.

TL;DR: This paper investigates the Heterogeneous Dial-A-Ride Problem (H-DARP) that consists of determining a vehicle route planning for heterogeneous users' transportation with a heterogeneous fleet of vehicles and proposes a hybrid Genetic Algorithm (GA) to solve the problem.

TL;DR: This paper addresses a sequence- and machine-dependent batch scheduling problem on a set of unrelated-parallel machines where the objective is to minimize a linear combination of total weighted completion time and total weighted tardiness.

TL;DR: The effectiveness of the proposed model has been evaluated on two test networks and the results suggest a step forward in the TSO/DSO coordination field, although further investigations to study the effect of assets with discrete control nature on the occurrence of disjoint flexibility areas should be carried.

TL;DR: An improved two-level heuristic to solve the clustered vehicle routing problem (CluVRP) by combining two variable neighborhood search algorithms, that explore the solution space at the cluster level and the individual customer level respectively.

TL;DR: Comprehensive review and evaluation of heuristics and meta-heuristics for the two-sided assembly line balancing problem and computational results demonstrate that the proper selection of encoding scheme, decoding procedure and objective function improves the performance of the algorithms by a significant margin.

TL;DR: A Two-Level VNS algorithm to solve the MT-VRPB efficiently and produced excellent results when tested on the special variant of the VRPB, which is useable for the classical VRPB.

TL;DR: A tabu search heuristic is proposed and embedded into a iterated local search to solve the multi-compartment vehicle routing problem (MCVRP), and it consistently produces solutions that are better than existing heuristic algorithms.

TL;DR: The VRP Spreadsheet Solver is found to be capable of solving Capacitated VRP and Distance-Constrained VRP instances with up to 200 customers within 1 h of CPU time.