Performance evaluation is critical for the design, planning and optimization in manufacturing systems. Accurate estimates of throughput rates and cycle time are particularly important for enterprises that providing customized products. A manufacturing system is an integrated system that couples material processing and material handling interdependently. There are a few studies on the performance modeling

Suppose that one is given a Vehicle Routing Problem (VRP) on a road network, but does not have access to detailed information about that network. One could obtain a heuristic solution by solving a modified version of the problem, in which true road distances are replaced with planar Euclidean distances. We test this heuristic, on two different types of VRP, using real road network data for twelve cities

In this paper we study a problem faced by network service providers in which a set of Virtual Network Functions (VNFs) has to be installed in a telecommunication network at minimum cost. For each given origin-destination pair of nodes (commodities), a latency-constrained routing path has to be found that visits the required VNFs in a pre-defined order. A limited number of functions can be installed

Postal and courier companies are under the pressure of minimizing operational costs while meeting requests for increasingly high service levels. We model their delivery problem as a dynamic multi-period general routing problem (DMPGRP) with the aim of minimizing the total cost over a given planning horizon. In most modern delivery systems, fluctuating demand volumes dynamically reveal themselves over

This paper focuses on the distributed concrete precast flow shop scheduling problem to minimize total weighted earliness and tardiness. It is crucial for a precast manufacturer to schedule jobs effectively to meet shipping dates because of tight due date, limited inventory capacity and huge tardiness penalties. In order to respond quickly to customer demands, many concrete precast manufacturers have

Reducing distribution costs is one of the effective ways for logistics enterprises to improve their core competitiveness. Aiming at the multi-depot vehicle routing problem under the time-varying road network, this paper proposes an integer programming model with the minimum total costs by comprehensively considering the fixed costs of vehicles, penalty costs on earliness and tardiness, fuel costs and

This paper explores a problem related to both the Traveling Salesman Problem and Scheduling Problem where a traveler moves through n locations (nodes), visits all locations and each location exactly once to assign and initiate one of n jobs, and then returns to the first location. After initiation of a job, the traveler moves to the next location immediately and the job continues autonomously. This

This paper introduces the Traveling Salesman Problem with Release Dates and Drone Resupply, which consists of finding a minimum time route for a single truck that can receive newly available orders en route via a drone sent from the depot. We assume that each order’s release date is known at the time of delivery planning. This context is common for many applications, notably last-mile logistics. We

The joint order batching and picker routing problem (JOBPRP) is a promising approach to minimize the order picking travel distance in a picker-to-parts warehouse environment. In this paper, we show that the JOBPRP can be modelled as a clustered vehicle routing problem (CluVRP), a variant of the capacitated VRP in which customers are grouped into clusters. To solve this cluster-based model of the JOBPRP

Recommendation system has attracted large amount of attention in the field of E-commerce research. Traditional MF (Matrix Factorization) methods take a global view on the user-item rating matrix to derive latent user vectors and latent item vectors for rating prediction. However, there is an inherent structure in the user-item rating matrix and a local correspondence between user clusters and item

We analyze customer losses in busy-periods of preemptive and non-preemptive oscillating MX/G/1/(n,a,b) systems. Specifically, we propose a recursive scheme to compute the probability function of the number of customer losses in busy-periods of such systems. The effectiveness and usefulness of the proposed method is illustrated through the presentation of numerical examples that consider different arrival

We address the problem of floorplanning, a crucial step of VLSI design, and propose a novel approach named Quasi-Newton-based FloorplannER (QinFer) for the challenging fixed-outline floorplanning problem. QinFer is an effective two-phase method. The first phase recursively bipartitions the original circuit to a set of subcircuits until each leaf subcircuit contains only one module. By placing each

In this article we consider how to construct schedules for the stacking and reclaiming activities of high-throughput dry-bulk export terminals (DBET) that operate large machines called stacker-reclaimers (SR) and handle iron ore, coking coal and thermal coal for export. In terminals with large and persistent stockpiles, the ever-changing geometry of stockpiles can impose challenging scheduling constraints

The multiple traveling salesmen problems (mTSP) are variants of the well-known traveling salesmen problems, in which n cities are to be assigned to m salespeople. In this paper, we propose an evolution strategy (ES) approach for solving the mTSP with minsum and minmax objectives. The ES employs a self-adaptive Ruin and Recreate (RR) heuristic to generate an offspring population. In the RR heuristic

The soft-clustered vehicle-routing problem (SoftCluVRP) is a variant of the classical capacitated vehicle-routing problem. Customers are partitioned into clusters and all customers of the same cluster must be served by the same vehicle. In this paper, we present a large multiple neighborhood search for the SoftCluVRP. We design and analyze multiple cluster destroy and repair operators as well as two

The low probability – high consequence nature of hazardous materials (hazmat) incidents dictate a risk-averse route planning approach. However, preparing routing plans for multiple hazmat shipments between various origin-destination pairs also raises the question of risk-equity, and not just minimization of hazmat risk. Hence, the objective is to plan an equitable routing plan for different rail hazmat

Credit risk evaluation is always the most important factor in determining Customers' credit status in financial institutions. Multi-Attribute Decision-Making (MADM) methods have been widely used in this field. But most of the studies neglect the undeniable impact of time and changes of the credit assessment criteria, their importance and evaluation data over time. On the other hand, developed Dynamic

We investigate a multiperiod drayage problem in which customers request transportation services over several days, possibly leaving the carrier some flexibility to change service periods. We compare three approaches for the problem: a path-based model with all feasible routes, a “Price-and-Branch” algorithm in which the pricing is formulated as a collection of shortest path problems in a cunningly

The nurse rostering problem is a very important problem to address. Due to the importance of nurses’ jobs, it is vital that all the nurses in a hospital are assigned to the most appropriate shifts and days so as to meet the demands of the hospital as well as to satisfy the requirements and requests of the nurses as much as possible. Nurse rostering is a computationally hard and challenging combinatorial

Mixed complementarity problems are of great importance in practice since they appear in various fields of applications like energy markets, optimal stopping, or traffic equilibrium problems. However, they are also very challenging due to their inherent, nonconvex structure. In addition, recent applications require the incorporation of integrality constraints. Since complementarity problems often model

In this paper, a new upper bound for the Multiple Knapsack Problem (MKP) is proposed, based on the idea of relaxing MKP to a Bounded Sequential Multiple Knapsack Problem, i.e., a multiple knapsack problem in which item sizes are divisible. Such a relaxation, called sequential relaxation, is obtained by suitably replacing the items of a MKP instance with items with divisible sizes. Experimental results

In this study we consider the shortest path problem, where the arc costs are subject to distributional uncertainty. Basically, the decision-maker attempts to minimize her worst-case expected loss over an ambiguity set (or a family) of candidate distributions that are consistent with the decision-maker’s initial information. The ambiguity set is formed by all distributions that satisfy prescribed linear

The Multi-Sector Planning (MSP) concept, adopted in both the SESAR and NextGen projects, promotes the control of aircraft and resolution of conflicts over a medium time horizon to reduce and balance controller workload. In the context of MSP, we propose a first formulation of the complexity resolution problem that allows trajectory modifications using both speed and heading changes assuming exact knowledge

This paper studies a new lot-size inventory problem for products whose demand pattern is dependent on price, advertising frequency and time. It is considered that the demand rate of an item multiplicatively combines the effects of a power function dependent on the frequency of advertisement and a function dependent on both selling price and time. This last function is additively separable in two power

To transfer export cars on board of car carrier vessels in vehicle transshipment terminals or to rebalance the vehicles of car sharing providers in urban areas, plenty of car relocation moves need to be processed. Often in these settings, a team of drivers cooperates to execute a given set of car movements. They are chauffeured by a taxi towards their dedicated cars. Once dropped off, a relocator executes

This paper addresses the development of conflict graph-based algorithms and data structures into the COIN-OR Branch-and-Cut (CBC) solver, including: (i) an efficient infrastructure for the construction and manipulation of conflict graphs; (ii) a preprocessing routine based on a clique strengthening scheme that can both reduce the number of constraints and produce stronger formulations; (iii) a clique

Memorization, as an algorithm design technique, enables to speed up algorithms at the price of increased space usage. In this work, we focus on search tree algorithms applied to sequencing problems. In these algorithms, on lower branching levels, isomorphic sub-problems may appear exponentially many times and the use of memorization is twofold: on the one hand it avoids repetitive solutions, as they

In 2005, David Pisinger asked the question “where are the hard knapsack problems?”. Noting that the classical benchmark test instances were limited in difficulty due to their selected structure, he proposed a set of new test instances for the 0–1 knapsack problem with characteristics that made them more challenging for dynamic programming and branch-and-bound algorithms. This important work highlighted

In this study, one-dimensional marble plane cutting problem is studied based on the cutting equipment productivity and effective use of marble blocks. Different types of marble planes should be cut from multiple stock sized marble blocks in parallel by using a stone block-cutting machine (gang saw). Marble blocks, which have different dimensions, and quality gradations are supplied by the marble processing

In this paper, we study a generalized single-batch-processing machine (SBPM) scheduling problem. Given a set of jobs that differ in terms of size, processing time and due date, the generalized SBPM problem aims to cluster the jobs into batches and process each batch one at a time on a capacitated batch-processing machine such that the total earliness and tardiness of jobs, a just-in-time objective

In this paper, we consider the medical student scheduling problem, which is a tactical scheduling problem assigning medical students to specific disciplines and hospitals in order to ensure an appropriate training over a one-year scheduling horizon. These internship positions are offered by local hospitals that specify minimum and maximum staffing requirements. To some extent, students can customise

The Steiner Team Orienteering Problem (STOP) is defined on a digraph in which arcs are associated with traverse times, and whose vertices are labeled as either mandatory or profitable, being the latter provided with rewards (profits). Given a homogeneous fleet of vehicles M, the goal is to find up to m=|M| disjoint routes (from an origin vertex to a destination one) that maximize the total sum of rewards

Project managers are often responsible for the management of multiple projects and associated personnel budgeting decisions. In order to determine the workforce size and mix accurately, we integrate the multi-project scheduling problem and personnel staffing problem. We construct a baseline personnel roster that takes the personnel scheduling constraints into account and model the workload stemming

This paper addresses the Single Container Loading Problem. We present an exact approach that considers the resolution of integer linear programming and constraint programming models iteratively. A linear relaxation of the problem based on packing in planes is proposed. Moreover, a comprehensive set of mathematical formulations for twelve practical constraints that arise in this problem are discussed

This paper introduces the heterogeneous fleet vehicle routing problem with multiple cross-docks, a variant of the vehicle routing problem with cross-docking, which considers the use of multiple cross-docks and a heterogeneous fleet of vehicles in a distribution system. A mixed integer linear program and an adaptive neighborhood simulated annealing algorithm are developed for the problem. The proposed

We consider a recently introduced class of network construction problems where edges of a transportation network need to be constructed by a server (construction crew). The server has a constant construction speed which is much lower than its travel speed, so relocation times are negligible with respect to construction times. It is required to find a construction schedule that minimizes a non-decreasing

This paper studies the problem of creating an optimal flight schedule for a heterogeneous fleet of helicopters tasked with transporting personnel to, from, and between offshore installations. The problem can be modelled as a rich vehicle routing problem and combines the following properties from the vehicle routing literature: pickup and delivery structure, heterogeneous fleet operating out of multiple

We study a Resilient Path Selection Problem (RPSP) arising in the design of communication networks with reliability guarantees. A graph is given, in which every arc has a cost and a probability of failure, and in which two nodes are marked as source and destination. The aim of our RPSP is to find a subgraph of minimum cost, containing a set of paths from the source to the destination nodes, such that

This paper addresses the container liner shipping network design by explicitly taking into account shipper's inertia preference and non-inertial preference. Firstly, using the double-constrained gravity model and Newton calibration method to predict the future OD demand matrix which is considered as the input of the model, and then the liner shipping company profit maximization is taken as the objective

In this paper, we study the duration-minimizing time-dependent vehicle routing problem with time windows (DM-TDVRPTW), where time-dependent travel times represent different levels of road congestion throughout the day. The departure time from depot becomes an important decision to reduce the route duration. We provide an alternative arc-based mixed-integer programming model with explicit arc time zone

In this paper, we address a variant of a batch scheduling problem with identical parallel machines and non-anticipatory family setup times to minimize the total weighted completion time. We developed an ILS and a GRASP matheuristics to solve the problem using a constructive heuristic and two MIP-based neighborhood searches, considering two batch scheduling mathematical formulations. The problem derives

Vehicle routing problems arise in many practical situations in the context of transportation logistics. Among them, we can highlight the problem of transporting customers from origin to destination locations, which is known as the dial-a-ride problem (DARP). This problem consists of designing least-cost routes to serve pickup-and-delivery requests, while meeting capacity, time window, maximum route

We present two new algorithms for a class of single-objective non-linear optimization problems, the so-called Mixed Integer Linear minimum Multiplicative Programs (MIL-mMPs). This class of optimization problems has a desirable characteristic: a MIL-mMP can be viewed as a special case of the problem of optimization over the efficient set in multi-objective optimization. The proposed algorithms exploit

We present a method for bundling scenarios in a progressive hedging heuristic (PHH) applied to stochastic service network design, where the uncertain demand is represented by a finite number of scenarios. Given the number of scenario bundles, we first calculate a vector of probabilities for every scenario, which measures the association strength of a scenario to each bundle center. This membership

This paper investigates the multi-route planning problem of multimodal transportation for oversize and heavyweight cargo based on reconstruction (MM-OHC-R). Considering required reconstruction of lines or nodes, a reconstruction model for route planning of OHC is proposed. The model aims to simultaneously determine the transportation route, modes of transport as well as the lines or nodes required

This article presents a novel scheduling approach to minimise the energy consumption of a machine during its idle periods. In the scheduling domain, it is common to model the behaviour of the machine by defining a small set of machine modes, e.g. “on”, “off” and “stand-by”. Then the transitions between the modes are represented by a static transition graph. In this paper, we argue that this type of

In an observable queue, customers joining decisions may be influenced by wait-aversion and crowd-attraction. These opposing phenomena and the diversity of arriving customers lead to an arrival process that depends on the number of present customers. For the system manager, having more customers may be beneficial as it can increase future arrivals due to the attraction generated. It may also saturate

Modern warehousing systems for fresh and cold-keeping storage, have presented characteristics of complex operation procedures, accelerated operating pace, and high labour intensity. Thus, the working environment has become complicated and hazardous. Two recent fatal accidents that occurred in cold warehouses have shifted wide focus to safety management. The invisibility of operators’ status and location

This paper addresses a mixed-integer linear programming model for solving the Multidimensional Multi-Way Number Partitioning Problem (MDMWNPP), the most general version of the family of Number Partitioning Problems. First, a contextualization concerning the Two-Way Number Partitioning Problem (TWNPP), the Multi-Way Number Partitioning Problem (MWNPP), the Multidimensional Two-Way Number Partitioning

We present in this paper a generalization of the one-commodity pickup and delivery traveling salesman problem where each customer supplies or demands a given amount of a certain product. The objective is to design a minimum cost two-echelon transportation network. The first echelon is the route of a capacitated vehicle that visits some customers, and the second echelon consists in the allocation of

We consider tandem queues with failures and a buffer of finite capacity at each service station. The service and repair time distributions of each server is of the phase type. A unified method for approximating the system under three types of service-failure interactions is presented. The approximation is based on the decomposition method. Some numerical examples are presented to investigate the effectiveness

The obnoxious p-median problem (OpM) is to determine a set of opened facilities such that the sum of distances between each client and the opened facilities is maximized. OpM is a general model that has a wide range of practical applications. However the problem is computationally challenging because it is known to be NP-hard. In this work, we propose an effective parallel iterative solution-based

Back in the 80’s clustering methods were considered state of the art for non-structured box constrained global optimization (GO). Their disappearance is mainly due to their increasing difficulties in solving even moderately sized GO problems, yet the basic idea was indeed a brilliant one. More recently population methods and Differential Evolution (DE) in particular has gained much attention in the

Drones are projected to alter last-mile delivery, but their short travel range is a concern. This study proposes a drone delivery network design using automated battery swapping machines (ABSMs) to extend ranges. The design minimizes the long-term delivery costs, including ABSM investment, drone ownership, and cost of the delivery time, and locates ABSMs to serve a set of customers. We build a mixed-integer

The contemporary decision making environment is becoming increasingly more automated. Developments in artificial intelligence, machine learning, and operations research have increased the prevalence of computer systems in decision making tasks across a myriad of applications. Markov decision processes (MDPs) are utilized in a variety of system controllers, and attacks against them are of particular

This paper addresses the long-term scheduling of pumping and delivery operations on straight multiproduct pipeline systems connecting multiple-sources to multiple-destinations. A generic solution framework is proposed, combining heuristic procedures and mixed integer linear programming (MILP) models. The pipeline scheduling problem is decomposed into two sub-problems: the allocation and sequencing

The job Sequencing and tool Switching Problem (SSP) has been extensively studied in the field of operations research, due to its practical relevance and methodological interest. Given a machine that can load a limited amount of tools simultaneously and a number of jobs that require a subset of the available tools, the SSP seeks a job sequence that minimizes the number of tool switches in the machine

This paper addresses a version of the single-facility Maximal Covering Location Problem on a network where the demand is: i) distributed along the edges and ii) uncertain with only a known interval estimation. To deal with this problem, we propose a minmax regret model where the service facility can be located anywhere along the network. This problem is called Minmax Regret Maximal Covering Location

We study a problem in which independent project managers cooperate to generate additional revenue by reallocating their resources. This additional revenue equals the increase in the direct return of a project minus the resource transfer cost. For each project, its direct return is closely related to its duration, which is mainly determined by the amount of resources available. In practice, the relationship

The location–routing problem (LRP) unites two important challenges in the design of distribution systems: planning the delivery of goods to customers (i.e., the routing of the delivery vehicles) and determining the locations of the depots from where these deliveries are executed. In this paper, we design an efficient and effective heuristic for the LRP based on an existing heuristic to solve the capacitated