TL;DR: A real-value version of particle swarm optimization (PSO) algorithm for solving the vehicle routing problem with simultaneous pickup and delivery (VRPSPD) and the mechanism of the PSO for solving VRPSPD is explained and demonstrated.

TL;DR: This paper focuses on detecting critical nodes, or nodes whose deletion results in the minimum pair-wise connectivity among the remaining nodes, and proposes a heuristic for the problem which exploits the combinatorial structure of the graph.

TL;DR: This paper presents an FMEA using the evidential reasoning (ER) approach, a newly developed methodology for multiple attribute decision analysis and is illustrated with an application to a fishing vessel.

TL;DR: A nonlinear mathematical model to consider production scheduling and vehicle routing with time windows for perishable food products in the same framework to maximize the expected total profit of the supplier is proposed.

TL;DR: This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP) using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm.

TL;DR: Two novel extensions for the well known ant colony optimization (ACO) framework are introduced here, which allow the solution of mixed integer nonlinear programs (MINLPs) and a hybrid implementation based on this extended ACO framework, specially developed for complex non-convex MINLPs is presented.

TL;DR: In this survey, a classification of 24 asymmetric traveling salesman problem (ATSP) formulations is presented and the strength of their LP relaxations is discussed and known relationships from the literature are reviewed.

TL;DR: The approach provides an example where an ACO algorithm successfully combines two completely different heuristic measures (with respect to loading and routing) within one pheromone matrix, which clearly outperforms previous heuristics from the literature.

TL;DR: The model is a multi-objective, mixed-integer, multiple-commodity network flow problem, which adopts the weighting method and develops a heuristic to efficiently solve this problem in practice and shows the model and the solution algorithm could be useful in practice.

TL;DR: This work considers a standard label correcting and label setting method, a purely enumerative near shortest path approach, and the two phase method, investigating different approaches to solving problems arising in phases 1 and 2 of the biobjective shortest path problem.

TL;DR: The proposed ACS algorithm uses a construction rule as well as two multi-route local search schemes to solve the vehicle routing problem with simultaneous delivery and pickup (VRPSDP) which is a combinatorial optimization problem.

TL;DR: Numerical tests show that simulation optimization method can solve the scheduling problem of container terminals efficiently and the surrogate model can improve the computation efficiency of simulation optimization.

TL;DR: A mathematical model and a genetic algorithm (GA) for two-sided assembly line balancing (two-ALB) are presented and the experimental results show that the proposed GA outperforms the heuristic and the compared GA.

TL;DR: This paper model the network retrofit problem as a two-stage stochastic programming problem that optimizes a mean-risk objective of the system loss and develops an efficient algorithm to efficiently handle the binary integer variables in the first stage and the nonlinear recourse in the second stage of the model formulation.

TL;DR: An open queuing network model of an emergency department (ED) design intended to increase the capacity of an ED to treat patients is derived through an operational research method that customizes to any hospital through the use of hospital-specific data elements.

TL;DR: In this paper, a fix-and-optimize algorithm for the dynamic multi-level capacitated lot sizing problem with setup carry-overs (MLCLSP-L) is presented.

TL;DR: This paper investigates how to sequence surgical cases in a day-care facility and applies column generation to solve this combinatorial optimization problem and proposes a dynamic programming algorithm to solve the pricing problem.

TL;DR: It will be shown that in an environment, which contains important features of the real-life retail environment, this new policy leads to substantial cost reductions compared with a base policy that does not take into account the age of inventories.

TL;DR: This study applies a simulated annealing (SA) heuristic to the truck and trailer routing problem (TTRP) and obtained 17 best solutions to the 21 benchmark TTRP benchmark problems, including 11 new best solutions.

TL;DR: The stochastic p-hub center problem with chance constraints is presented, which is used to model the service-level guarantees of small package delivery companies and discusses analytical results, proposed solution heuristics, and the results from computational experiments.

TL;DR: This paper considers the resource-constrained project scheduling problem with multiple execution modes for each activity and minimization of the makespan, and proposes a differential evolution (DE) algorithm to solve the problem within small time per activity.

TL;DR: An artificial neural network (ANN) designed to forecast demand volume of specific areas during different times of the day is compared to current industry practice for accuracy of prediction and shows that both methods produce accurate forecasts for certain levels of time and space granularity.

TL;DR: A mixed integer programming is presented and solved by CPLEX for small scale instances and four heuristics are proposed to investigate the performance for moderate and large scale instances of the two-stage hybrid cross docking scheduling problem.

TL;DR: A new iterative heuristic for the two-dimensional knapsack problem based on the sequence pair representation proposed by Murata et al. is presented and able to handle problem instances where rotation is allowed.

TL;DR: A mathematical formulation of the Petrol Station Replenishment Problem with Time Windows is proposed and two heuristics based on arc preselection and on route preselection are described, which show efficiency and distance reduction over a solution obtained by an experienced dispatcher.

TL;DR: A simulation study shows how a terminal's long-run average quay crane rate depends on (1) the length of the storage blocks in the terminal's container yard and (2) the system that deploys yard cranes amongBlocks in the same zone.

TL;DR: In this article, an integer programming model for the problem is presented, which is decomposed using Dantzig-Wolfe decomposition and solved by column generation in a branch-and-price framework.

TL;DR: A genetic algorithm is used to solve the problem of which orders to choose to maximize profit, when there is limited capacity and an order delivered after its due date incurs a tardiness penalty.

TL;DR: In this article, an ant colony optimization (ACO) algorithm is proposed for operations of steady flow gas pipeline, which is composed of compressing stations linked by pipelegs and the objective function is the power consumed in the system by these stations.