From the Publisher:
This book explores the meta-heuristics approach called tabu search, which is dramatically changing our ability to solve a hostof problems that stretch over the realms of resource planning,telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics,pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservationand scores of other problems. The major ideas of tabu search arepresented with examples that show their relevance to multipleapplications. Numerous illustrations and diagrams are used to clarifyprinciples that deserve emphasis, and that have not always been wellunderstood or applied. The book's goal is to provide ''hands-on' knowledge and insight alike, rather than to focus exclusively eitheron computational recipes or on abstract themes. This book is designedto be useful and accessible to researchers and practitioners inmanagement science, industrial engineering, economics, and computerscience. It can appropriately be used as a textbook in a masterscourse or in a doctoral seminar. Because of its emphasis on presentingideas through illustrations and diagrams, and on identifyingassociated practical applications, it can also be used as asupplementary text in upper division undergraduate courses. 

Finally, there are many more applications of tabu search than canpossibly be covered in a single book, and new ones are emerging everyday. The book's goal is to provide a grounding in the essential ideasof tabu search that will allow readers to create successfulapplications of their own. Along with the essentialideas,understanding of advanced issues is provided, enabling researchers togo beyond today's developments and create the methods of tomorrow.

Tabu Search

The theory of deterministic sequencing and scheduling has expanded rapidly during the past years. In this paper we survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory. Special cases considered are single machine scheduling, identical, uniform and unrelated parallel machine scheduling, and open shop, flow shop and job shop scheduling. We indicate some problems for future research and include a selective bibliography.

/pdf/optimization-and-approximation-in-deterministic-sequencing-327pfewdb6.pdf

Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey

The pickup and delivery problem with time windows is the problem of serving a number of transportation requests using a limited amount of vehicles. Each request involves moving a number of goods from a pickup location to a delivery location. Our task is to construct routes that visit all locations such that corresponding pickups and deliveries are placed on the same route, and such that a pickup is performed before the corresponding delivery. The routes must also satisfy time window and capacity constraints.

This paper presents a heuristic for the problem based on an extension of the large neighborhood search heuristic previously suggested for solving the vehicle routing problem with time windows. The proposed heuristic is composed of a number of competing subheuristics that are used with a frequency corresponding to their historic performance. This general framework is denoted adaptive large neighborhood search.

The heuristic is tested on more than 350 benchmark instances with up to 500 requests. It is able to improve the best known solutions from the literature for more than 50% of the problems.

The computational experiments indicate that it is advantageous to use several competing subheuristics instead of just one. We believe that the proposed heuristic is very robust and is able to adapt to various instance characteristics.

/pdf/an-adaptive-large-neighborhood-search-heuristic-for-the-54a14dq2lk.pdf

An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows

/pdf/sequencing-and-scheduling-algorithms-and-complexity-lnutyrr3kz.pdf

Sequencing and scheduling: algorithms and complexity

https://ira.lib.polyu.edu.hk/bitstream/10397/1269/1/SetupSurvey-2006%28June-19%29.pdf

A survey of scheduling problems with setup times or costs

The pickup and delivery problem with time windows requires that a group of vehicles satisfy a collection of customer requests. Each customer request requires the use of a single vehicle both to load a specified amount of goods at one location and to deliver them to another location. All requests must be performed without violating either the vehicle capacity or the customer time window stipulated at each location. In this paper, we present a reactive tabu search approach to solve the pickup and delivery problem with time windows using three distinct move neighborhoods that capitalize on the dominance of the precedence and coupling constraints. A hierarchical search methodology is used to dynamically alternate between neighborhoods in order to negotiate different regions of the solution space and adjust search trajectories. In order to validate our technique's effectiveness, we have constructed a new set of benchmark problems for the pickup and delivery problem with time windows based on Solomon's benchmark vehicle routing problem with time windows data sets. Computational results substantiate the solution quality and efficiency of our reactive tabu search approach.

/pdf/solving-the-pickup-and-delivery-problem-with-time-windows-4lj9b1tnte.pdf

Solving the pickup and delivery problem with time windows using reactive tabu search

In the job shop scheduling problem we desire to minimize the makespan where a set of machines perform technologically ordered operations unique to each member of a set of jobs. Each operation has a fixed time duration, no machine can perform more than one operation at a time, and preemption is not allowed. In this paper, an effective tabu search approach to the job shop scheduling problem is presented. The procedure starts from the best solution rendered by a set of 14 heuristic dispatching solutions. It then makes use of the classical disjunctive network representation of the problem and iteratively moves to another feasible solution by reversing the order of two adjacent critical path operations performed by the same machine. The concepts of historical generators and search restart are used in conjunction with a contiguous spectrum of short term memory values to enhance the overall exploration strategy. Computational results are presented and areas for future investigation are suggested.

Solving the job shop scheduling problem with tabu search

In this paper we discuss the use of three local search strategies within a tabu search (TS) method for the approximate solution of a single machine scheduling problem. The problem consists of minimizing the sum of the set-up costs and linear delay penalties whenN jobs, arriving at time zero, are to be scheduled for sequential processing on a continuously available machine. Following a review of a previous study of this problem, we first consider a TS method that uses the common approach of making a succession of pairwise job exchanges, or swaps, to move from one trial solution to another. Next, we consider the use of insert moves to define the local neighborhood of each trial solution. These moves consist of transferring a single job from one position to another in the schedule. Finally, we construct a TS method (TS-hybrid) that employs both swap and insert moves. Experiments with benchmark problems of up to 60 jobs illustrate that there is an advantage in using more than one strategy to move from one trial solution to another within a TS method.

Tabu search methods for a single machine scheduling problem

An essential first step in the design of a municipal water distribution system is the determination of the locational placement or layout of the links of pipe that will form the system. A two-level hierarchically integrated system of models is developed for the layout of both single and multiple source water distribution systems. The first level, a nonlinear programming model, selects an economical tree layout for the major pipe links. The second level, an integer programming model, chooses the loop- forming links to add to the first level tree layout in order to minimize the cost of providing a specified level of reliability in case of failure of the larger first level links. The system of models is applied to an example two-source water distribution system layout problem.

Obtaining the Layout of Water Distribution Systems

ConsNet is a comprehensive software package for the design of conservation area networks (CANs). The software selects areas to be potentially placed under conservation management for the representation of biodiversity surrogates. Additionally, ConsNet optimizes spatial criteria including compactness, connectivity, replication, and alignment, as well as socio-economic criteria as specified by users. ConsNet uses an advanced tabu search engine to identify efficient alternatives quickly, offering capabilities beyond existing planning software. The ability to perform ongoing interactive analysis with multi-criteria objectives makes ConsNet an ideal decision support tool for large scale planning exercises.

J. Wesley Barnes

Papers

Solving the pickup and delivery problem with time windows using reactive tabu search

Solving the job shop scheduling problem with tabu search

Tabu search methods for a single machine scheduling problem

Obtaining the Layout of Water Distribution Systems

ConsNet: new software for the selection of conservation area networks with spatial and multi‐criteria analyses