Batch machine production with perishability time windows and limited batch size

This article provides a theoretical analysis of the problem of scheduling jobs in batches by family on a batch-processing machine, in the presence of perishability time windows of equal length. The problem arises in the context of production planning in a microbiological laboratory, and has application in wafer-fab production and for wireless broadcasting. The combined features of multiple families and time windows are new to the literature. The study is restricted to unit job processing times. We prove that the problem is NP-hard, thus solving an open problem by Uzsoy [24]. A Dynamic Programme is developed, with running time polynomial in the input variables of maximum batch size, the number of families and the length of the demand time horizon. In addition, we show that an heuristic approach to minimising the perishability time window can provide a 2-approximation to the optimum.     

Analysis of job assignment with batch arrivals among heterogeneous servers

We revisit the problem of job assignment to multiple heterogeneous servers in parallel. The system under consideration, however, has a few unique features. Specifically, repair jobs arrive to the queueing system in batches according to a Poisson process. In addition, servers are heterogeneous and the service time distributions of the individual servers are general. The objective is to optimally assign each job within a batch arrival to minimize the long-run average number of jobs in the entire system. We focus on the class of static assignment policies where jobs are routed to servers upon arrival according to pre-determined probabilities. We solve the model analytically and derive the structural properties of the optimal static assignment. We show that when the traffic is below a certain threshold, it is better to not assign any jobs to slower servers. As traffic increases (either due to an increase in job arrival rate or batch size), more slower servers will be utilized. We give an explicit formula for computing the threshold. Finally we compare and evaluate the performance of the static assignment policy to two dynamic policies, specifically the shortest expected completion policy and the shortest queue policy.     

Minimizing total earliness and tardiness on re-entrant batch processing machine with time windows

The time window (TW) generalizes the concept of due date. The semiconductor wafer fabrication system is currently one of the most complex production processes, which has typical re-entrant batch processing machine (RBPM). RBPM is a bottleneck. This paper addresses a scheduling of RBPM with job-dependent TWs. According to a general modelling, an improved and new job-family-oriented modelling of the decomposition method that is based on the slack mixed integer linear programming is proposed. First, the complicated scheduling problem of RBPM is divided into sub-problems, which are executed circularly. Then, each one consists of updating, sequencing and dispatching. The objective is to minimize the total earliness and tardiness for job-dependent TWs. In order to evaluate the proposed modelling, the experiments are implemented on the real-time scheduling simulation platform and optimization toolkit ILOG CPLEX. The results show that the improved modelling obtains better solutions in less computation time.     

Manpower allocation with time windows

In this paper, we propose a manpower allocation model with time windows which is of practical interest. This model originates from a real-life port manpower allocation problem where demand is generated from locations in the yard for servicemen who are dispatched from a central point and where the objectives are to minimize the number of servicemen used, travel distances, travel times and waiting times. We develop a tabu-embedded simulated annealing algorithm and a squeaky wheel optimization with local search algorithm for the problem. Experimental results are reported which show the effectiveness of our approaches.     

The secretary problem with multiple job vacancies and batch candidate arrivals

We extend the secretary problem with multiple vacancies to allow batch arrival of candidates. We establish structural properties of the optimal policies. We show that the optimal reward is convex and submodular in the values of candidates, which means that there is benefit for having a candidate pool with more variable or less interdependent values. Similar properties continue to hold when there are multiple classes of vacancies. Our model is applicable to recruitment, dynamic auctions and sequential investment.     

Batch scheduling with controllable setup and processing times to minimize total completion time

We study a problem of scheduling n jobs on a single machine in batches. A batch is a set of jobs processed contiguously and completed together when the processing of all jobs in the batch is finished. Processing of a batch requires a machine setup time dependent on the position of this batch in the batch sequence. Setup times and job processing times are continuously controllable, that is, they are real-valued variables within their lower and upper bounds. A deviation of a setup time or job processing time from its upper bound is called a compression. The problem is to find a job sequence, its partition into batches, and the values for setup times and job processing times such that (a) total job completion time is minimized, subject to an upper bound on total weighted setup time and job processing time compression, or (b) a linear combination of total job completion time, total setup time compression, and total job processing time compression is minimized. Properties of optimal solutions are established. If the lower and upper bounds on job processing times can be similarly ordered or the job sequence is fixed, then O(n³ log n) and O(n⁵) time algorithms are developed to solve cases (a) and (b), respectively. If all job processing times are fixed or all setup times are fixed, then more efficient algorithms can be devised to solve the problems.     

Methods for routing with time windows

Consider a set of trips where each trip is specified a priori by a place of origin, a destination, a duration, a cost and a time interval within which the trip must begin. The trips may include visits to one or more specific points. Our problem is to determine the number of vehicles required together with their routes and schedules, so that each trip begins within his given time interval, while the fixed costs related to the number of vehicles, and the travel costs between trips are minimized. The problem is a generalization of the m-travelling salesman problem.We compare numerical results for 3 algorithms developed by our research team:

• 1.(1) Column generation on a set partitioning problem solved by simplex and branch-and-bound; columns are generated by a shortest path algorithm with time constraints on the nodes.
• 2.(2) Adaptation of the Carpaneto-Toth algorithm for the asymmetric travelling salesman problem: solution of network problems by relaxing scheduling constraints, and branch-and-bound on flow variables.
• 3.(3) Solution of network problems by relaxing scheduling constraints and branch-and-bound based on dividing the time windows.

     

Crossdocking—JIT scheduling with time windows

In this paper, we study a problem central to crossdocking that aims to eliminate or minimize storage and order picking activity using JIT scheduling. The problem is modelled naturally as a machine scheduling problem. As the problem is NP-hard, and for real-time applications, we designed and implemented two heuristics. The first uses Squeaky Wheel Optimization embedded in a Genetic Algorithm and the second uses Linear Programming within a Genetic Algorithm. Both heuristics offer good solutions in experiments where comparisons are made with the CPLEX solver.     

Lot-sizing with production and delivery time windows

We study two different lot-sizing problems with time windows that have been proposed recently. For the case of production time windows, in which each client specific order must be produced within a given time interval, we derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs. For the variant with nonspecific orders, known to be equivalent to the problem in which the time windows can be ordered by time, we also show equivalence to the basic lot-sizing problem with upper bounds on the stocks. Here we derive polynomial time dynamic programming algorithms and tight extended formulations for the uncapacitated and constant capacity problems with general costs. For the problem with delivery time windows, we use a similar approach to derive tight extended formulations for both the constant capacity and uncapacitated problems with Wagner-Whitin (non-speculative) costs. We are most grateful for the hospitality of IASI, Rome, where part of this work was carried out. The collaboration with IASI takes place in the framework of ADONET, a European network in Algorithmic Discrete Optimization, contract n MRTN-CT-2003-504438. This text presents research results of the Belgian Program on Interuniversity Poles of Attraction initiated by the Belgian State, Prime Minister's Office, Science Policy Programming. The scientific responsibility is assumed by the authors.     

The Delivery Man Problem with time windows

In this paper, a variant of the Traveling Salesman Problem with Time Windows is considered, which consists in minimizing the sum of travel durations between a depot and several customer locations. Two mixed integer linear programming formulations are presented for this problem: a classical arc flow model and a sequential assignment model. Several polyhedral results are provided for the second formulation, in the special case arising when there is a closed time window only at the depot, while open time windows are considered at all other locations. Exact and heuristic algorithms are also proposed for the problem. Computational results show that medium size instances can be solved exactly with both models, while the heuristic provides good quality solutions for medium to large size instances.     

Real-time vehicle rerouting problems with time windows

This paper introduces and studies real-time vehicle rerouting problems with time windows, applicable to delivery and/or pickup services that undergo service disruptions due to vehicle breakdowns. In such problems, one or more vehicles need to be rerouted, in real-time, to perform uninitiated services, with the objective to minimize a weighted sum of operating, service cancellation and route disruption costs. A Lagrangian relaxation based-heuristic is developed, which includes an insertion based-algorithm to obtain a feasible solution for the primal problem. A dynamic programming based algorithm solves heuristically the shortest path problems with resource constraints that result from the Lagrangian relaxation. Computational experiments show that the developed Lagrangian heuristic performs very well.     

Minimizing makespan and total completion time for parallel batch processing machines with non-identical job sizes

This paper considers the scheduling problem of parallel batch processing machines with non-identical job sizes. The jobs are processed in batches and the machines have the same capacity. The models of minimizing makespan and total completion time are given using mixed integer programming method and the computational complexity is analyzed. The bound on the number of feasible solutions is given and the properties of the optimal solutions are presented. Then a polynomial time algorithm is proposed and the worst case ratios for minimizing total completion time and makespan is proved to be 2 and (8/3–2/3 m) respectively. To test the proposed algorithm, we generate different levels of random instances. The computational results demonstrate the effectiveness of the algorithm for minimizing the two objectives.     

Batch processor sharing with hyper-exponential service time

We study the Processor Sharing queueing model with a hyper-exponential service time distribution and Poisson batch arrival process. In the case of the hyper-exponential service time distribution we find an analytical expression for the expected conditional response time function and obtain an alternative proof of its concavity with respect to the service time.     

The vehicle routing problem with coupled time windows

In this article we introduce the vehicle routing problem with coupled time windows (VRPCTW), which is an extension of the vehicle routing problem with time windows (VRPTW), where additional coupling constraints on the time windows are imposed. VRPCTW is applied to model a real-world planning problem concerning the integrated optimization of school starting times and public bus services. A mixed-integer programming formulation for the VRPCTW within this context is given. It is solved using a new meta-heuristic that combines classical construction aspects with mixed-integer preprocessing techniques, and improving hit-and-run, a randomized search strategy from global optimization. Solutions for several randomly generated and real-world instances are presented.     

The open vehicle routing problem with time windows

In this paper, we consider the open vehicle routing problem with time windows (OVRPTW). The OVRPTW seeks to find a set of non-depot returning vehicle routes, for a fleet of capacitated vehicles, to satisfy customers’ requirements, within fixed time intervals that represent the earliest and latest times during the day that customers’ service can take place. We formulate a comprehensive mathematical model to capture all aspects of the problem, and incorporate in the model all critical practical concerns. The model is solved using a greedy look-ahead route construction heuristic algorithm, which utilizes time windows related information via composite customer selection and route-insertion criteria. These criteria exploit the interrelationships between customers, introduced by time windows, that dictate the sequence in which vehicles must visit customers. Computational results on a set of benchmark problems from the literature provide very good results and indicate the applicability of the methodology in real-life routing applications.     

Local search in routing problems with time windows

We develop local search algorithms for routing problems with time windows. The presented algorithms are based on thek-interchange concept. The presence of time windows introduces feasibility constraints, the checking of which normally requires O(N) time. Our method reduces this checking effort to O(1) time. We also consider the problem of finding initial solutions. A complexity result is given and an insertion heuristic is described.     

Resource levelling for projects with schedule-dependent time windows

The paper presents polynomial heuristic procedures for different types of resource levelling problems for projects with minimum and maximum time lags between project activities. Both problems without and with explicit resource constraints are treated. Thus far, only pseudopolynomial heuristics for special resource levelling problems without maximum time lags and resource constraints have been proposed. An experimental performance analysis shows that the new heuristics approximately solve problem instances with up to 500 activities and five resources within reasonable computing time.