A flight scheduling model for Taiwan airlines under market competitions

In this research, we develop a short-term flight scheduling model with variable market shares in order to help a Taiwan airline to solve for better fleet routes and flight schedules in today's competitive markets. The model is formulated as a non-linear mixed integer program, characterized as an NP-hard problem, which is more difficult to solve than the traditional fixed market share flight scheduling problems, often formulated as integer/mixed integer linear programs. We develop a heuristic method to efficiently solve the model. The test results, mainly using the data from a major Taiwan airline's operations, show the good performance of the model and the solution algorithm.     

An investigation into a new class of vehicle routing problem with backhauls

A new version of the vehicle routing problem with backhauls is presented. In this new problem backhauls are not restricted to be visited once all linehaul customers have been served, neither are backhaul customers fully mixed with linehaul customers. In this problem the user based on his or her experience, the vehicle capacity, the type of products and the type of vehicle used, can define the position along a route from which the first backhaul customer may be visited. An insertion-type heuristic is put forward for this class of problems. An analysis of the improvement in route cost obtained by allowing a relaxation in the restriction of the mix of linehaul and backhaul customers is reported.     

不确定需求下的冷链分销商最优决策

针对新鲜产品供应链 (冷链) 中分销商, 引入保鲜努力刻画分销商投入的保鲜工作, 考虑新鲜产品到达市场的数量与质量, 分析冷链分销商的最优决策问题.与前人研究相比, 本文使用加法形式需求函数刻画市场需求, 并使用相关企业数据验证加法形式需求函数合理性, 完善了冷链分销商决策问题的相关研究.研究发现, 当保鲜努力外生时, 分销商的最优订货数量和最优零售价格只与保鲜努力有关;当零售价格外生时, 分销商的最优保鲜努力与产品实际单位成本关于保鲜努力函数的一阶最优条件有关;当订货数量外生时, 分销商制定的零售价格随保鲜努力增加而增大, 所获得的利润也随保鲜努力递增, 但边际利润随保鲜努力递减.最后, 将所得结论应用于中国500强民营企业卓尔控股有限公司旗下的小雪冷链 (武汉) 物流有限公司, 为该公司提供相应的保鲜努力投入策略.     

Integrated project operations and personnel scheduling with multiple labour classes

The main theme of this paper is improving project schedules by integrating the scheduling of project jobs and labour resources. An ILP model is presented of the integrated project operations and personnel scheduling problem with multiple labour categories. Traditionally, this problem is solved in two steps: first, operations are scheduled by solving the resource-constrained project scheduling problem; then, labour categories are scheduled by solving the personnel days-off scheduling problem. The proposed model combines the two stages into an integrated problem, which is solved in one step. Using 48 test problems, the two methods were compared in terms of total cost, labour cost and scheduling efficiency. The results clearly indicate that the integrated model outperforms the traditional two-step method.     

Knowledge-based system for selection of an AGV and a workcentre for transport of a part in on-line scheduling of FMS

The operational level of flexible manufacturing systems FMS is concerned with the detailed decision making required for real-time operation. The real-time control of FMS is extremely complex. On-line scheduling is referred to as real-time control of FMS. On-line scheduling of an FMS requires decision making in various scheduling problems such as selection of an AGV and a workcentre from a set of workcentres simultaneously requesting the service for transport of a part, selection of a new part type to be released into the system, etc. This paper describes a prototype knowledge-based system for selection of an AGV and a workcentre from a set of workcentres simultaneously requesting the service for transport of a part in on-line scheduling of FMS. The knowledge-based system is evaluated by the empirical approach. On-line scheduling of FMS gives potential advantages such as productivity and low throughput time.     

Single-machine scheduling with general sum-of-processing-time-based and position-based learning effects

In this paper, we propose a new learning effect model in which the actual job processing time is a general function of the normal processing time of jobs already processed and its scheduled position. This model has the advantage that different learning curves can be constructed easily, such as the plateau function. It is found that most of the models in the literature are special cases of our proposed model. The optimal sequences for some single-machine problems are then provided.     

Real-time scheduling and control of one-of-a kind production

Due to the great diversity of product types in one-of-a-kind production (OKP), the production scheduling and control in OKP is much more difficult than production scheduling and control of other production systems, e.g. mass production and batch production. Hence, the production efficiency in OKP companies is relatively lower. To improve productivity in OKP, a dynamic hierarchy production control system is presented. Using this control structure, a production system in an OKP company can be flexibly organized or re-organized according to the structure of a customized product (or an OKP product). Production synchronizing and scheduling algorithms for OKP shop floor production control are presented. Using these algorithms, a cybernetic model can be developed for shop floor control in OKP. The algorithms are applied to two alternate production scheduling goals in OKP, namely ASAP (as soon as possible) production and JIT (just in time) production.     

A heuristic for scheduling in a flowshop with the bicriteria of makespan and maximum tardiness minimization

This article deals with the development of a heuristic for scheduling in a flowshop with the objective of minimizing the makespan and maximum tardiness of a job. The heuristic makes use of the simulated annealing technique. The proposed heuristic is relatively evaluated against the existing heuristic for scheduling to minimize the weighted sum of the makespan and maximum tardiness of a job. The results of the computational evaluation reveal that the proposed heuristic performs better than the existing one.     

Subcontracting price schemes for order acceptance and scheduling

In this paper we study subcontracting price schemes between a subcontractor and a firm that are engaged in subcontracting of heterogeneous orders with distinct due dates, revenues, and processing times. We assume that the subcontractor proposes the subcontracting pricing and the firm follows by determining the subcontracted orders by solving its order acceptance and scheduling problem. When the subcontractor adopts a linear pricing scheme, we find the firm׳s optimal decisions and develop an algorithm to derive the subcontractor׳s own optimal pricing. We then design a fixed pricing with transfer payment scheme and a quantity discount pricing scheme to coordinate the firm׳s and subcontractor׳s decisions. We examine if the subcontractor can make a higher profit using either of these schemes than the linear pricing scheme, and if they will induce the firm to make decisions that lead to system-wide optimal outcomes.     

Planning a sustainable reverse logistics system: Balancing costs with environmental and social concerns

The present work aims to support tactical and operational planning decisions of reverse logistics systems while considering economic, environmental and social objectives. In the literature, when addressing such systems economic aspects have been often used, while environmental concerns have emerged only recently. The social component is the one less studied and rarely the combination of the three concerns has been analyzed. This work considers the three objectives and was motivated by the challenge of supporting decision makers when managing a real case study of a recyclable waste collection system, where strategic decisions on the number and location of depots, vehicles and containers were taken beforehand. Tactical and operational decisions are studied involving the establishment of service areas for each depot and the definition and scheduling of collection routes for each vehicle. Such decisions should represent a compromise solution between the three objectives translating a sustainable reverse logistics plan. The problem is modeled as a multi-objective, multi-depot periodic vehicle routing problem with inter-depot routes. A mathematical formulation and a solution approach are proposed. An approximation to the Pareto front is obtained for the case study and the trade-offs between the objectives are discussed. A balanced solution is proposed.     

Analysis of antithetic sequences in flowshop scheduling to minimize makespan

The antithetic properties of flowshop sequences are investigated to improve the classical Monte Carlo method for solving the n -job, m -machine problem with minimization of makespan. The major issues considered are (1) establishing a negative correlation of the makespan values of forward and reverse sequences; (2) developing the Antithetical Monte Carlo (AMC) method, which can be used to quickly estimate the mean of the makespan distribution by exploiting the antithetic property of sequences; (3) using AMC to find low makespan values; (4) determining a threshold value of makespan beyond which it would be likely to find an optimal or near optimal makespan when reversing a sequence. Statistical tests indicate that the performance of AMC is superior to that of the classical Monte Carlo method. Possible applications of this concept are discussed including extensions to other mathematical problems with antithetic properties.     

Minimizing takeoff and landing risk in helicopter pickup and delivery operations

The problem of minimizing total helicopter passenger risk caused by takeoffs and landings is studied. There are passenger pickup and delivery demands to be satisfied at given points by flights starting and ending in the same heliport and visiting several points. For each point, the delivery demand is the number of passengers to be transported from the heliport to this point and the pickup demand is the number of different passengers to be transported from this point to the heliport. Each pickup and delivery demand must be satisfied in full by one flight. There are an upper bound on the number of flights and an upper bound on the helicopter passenger capacity. The objective function is a linear combination of the numbers of passengers involved in takeoffs and landings at visited points. A solution is characterized by the number of flights, sets of visited points and their sequences for all flights. Properties of optimal solutions are established. Several cases are proved NP-hard. A quadratic boolean programming formulation and two dynamic programming algorithms are suggested for the general case. Computer experiments demonstrated that they are able to solve real-life instances. Polynomial time algorithms are presented for special cases. Implementation of the suggested solutions into the real helicopter operations should decrease the number of fatalities.     

Comparative evaluation of genetic algorithms for job-shop scheduling

Many optimization problems from the industrial engineering world, in particular the manufacturing systems, are very complex in nature and quite hard to solve by conventional optimization techniques. There has been increasing interest in imitating living beings to solve such kinds of hard optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization tech niques called evolutionary algorithms, which can often outperform conventional optimization methods when applied to difficult real-world problems. There are currently three main avenues of this research: genetic algorithms (GAs), evolutionary programming (EP) and evolution strategies (ESs). Among them, genetic algorithms are perhaps the most widely known types of evolutionary algorithms today. During the past years, several GAs for the job-shop scheduling problems have been proposed, each with different chromosome representation. In this paper, the different GAs are collected from the literature and an attempt has been made to evaluate them. The benchmark problems available in open literature are used for evaluation and the performance measure considered is makespan. The algorithms are coded in C+ +.     

An intelligent workstation controller for integrated planning and scheduling of FMS cell

This paper presents an experimental design developed to determine a combination of robust planning and scheduling rules for an intelligent workstation controller (IWC). The IWC is used as part of the control system for an automated flexible manufacturing system. A three-level hierarchical control structure (shop, workstation and equipment)is adopted in order effectively to control a shop-floor. At the top level is a shop controller which receives orders and their associated manufacturing information, and manages interactions among workstations. The IWC defines and resolves the production control activities necessary to coordinate a group of equipment controllers so as to ensure the completion of orders. Specifically, the IWC is responsible for selecting a specific process routeing for each part, allocating resources, scheduling and coordinating the activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports. These activities are accomplished using planning, scheduling, and execution functions. In order to demonstrate the effectiveness and robustness of the IWC, all the controllable and uncontrollable factors need to be identified and detailed. Controllable factors are those which are set by the controller and cannot be directly affected by the production environment. Uncontrollable factors are those which vary with the production environment and cannot be directly changed by the controller developer. The objective of the paper is to illustrate how a good set of controllable factors that dictate the IWC's effectiveness and robustness over various uncontrollable factors can be determined. Due to the number of possible combinations of all the factors, a complete validation of the effectiveness and robustness of the IWC is extremely time consuming and far beyond the scope of this paper. Therefore, a few planning and scheduling strategies are selected and a formal experiment is conducted. The experiment illustrates how significant performance dependencies for various planning and scheduling strategies can be identified.     

Cross dock scheduling: Classification,literature review and research agenda

At cross docking terminals incoming deliveries of inbound trucks are unloaded, sorted, moved across the dock and finally loaded onto outbound trucks, which immediately leave the terminal towards their next destination in the distribution chain. Accordingly, a cross dock is a consolidation point in a distribution network, where multiple smaller shipments can be merged to full truck loads in order to realize economies in transportation. In this context, the truck scheduling problem, which decides on the succession of truck processing at the dock doors, is especially important to ensure a rapid turnover and on-time deliveries. Due to its high real-world significance, several truck scheduling procedures have been introduced during recent years, which all treat specific cross dock settings. In order to structure and promote scientific progress, this paper introduces a classification of deterministic truck scheduling. With the help of this classification, existing literature is reviewed and future research needs are identified. Moreover, we represent a yet unexplored class of truck scheduling problems which is highly relevant in real-world distribution networks.     

Single-machine scheduling problems with the effects of learning and deterioration

In this paper, we consider the single-machine scheduling problems with the effects of learning and deterioration. By the effects of learning and deterioration, we mean that job processing times are defined by functions of their starting times and positions in the sequence. It is shown that even with the introduction of learning effect and deteriorating jobs to job processing times, single-machine makespan and sum of completion times (square) minimization problems remain polynomially solvable, respectively. But for the following objective functions: the weighted sum of completion times and the maximum lateness, this paper proves that the WSPT rule and the EDD rule can construct the optimal sequence under some special cases, respectively.     

Heuristics for scheduling in a flowshop with setup,processing and removal times separated

The problem of scheduling in a flowshop, where setup, processing and removal times are separable, is considered with the objective of minimizing makespan. Heuristic algorithms are developed by the introduction of simplifying assumptions into the scheduling problem under study. An improvement method is incorporated in the heuristics to enhance the quality of their solutions. The proposed heuristics and an existing heuristic are evaluated by a large number of randomly generated problems. The results of an extensive computational investigation for various values of parameters are presented.     

Online interval scheduling: randomized and multiprocessor cases

We consider the problem of scheduling a set of equal-length intervals arriving online, where each interval is associated with a weight and the objective is to maximize the total weight of completed intervals. An optimal 4-competitive algorithm has long been known in the deterministic case, but the randomized case remains open. We give the first randomized algorithm for this problem, achieving a competitive ratio of 3.5822. We also prove a randomized lower bound of 4/3, which is an improvement over the previous 5/4 result. Then we show that the techniques can be carried to the deterministic multiprocessor case, giving a 3.5822-competitive 2-processor algorithm, and a 4/3 lower bound for any number of processors. We also give a lower bound of 2 for the case of two processors. A preliminary version of this paper appeared in the Proceedings of COCOON 2007, LNCS, vol. 4598, pp. 176–186. The work described in this paper was fully supported by a grant from City University of Hong Kong (SRG 7001969), and NSFC Grant No. 70525004 and 70702030.