You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A review on integrated process planning and scheduling 
Chapter Title:  Non-linear Process Planning 
1. Abstract of Cited Paper (BIB001):  A job-shop scheduling method is described utilizing a negotiation-based algorithm in autonomous distributed systems. Elements of a production system such as jobs and machines are regard as agents that act like an independent profit maker. A negotiation procedure is suggested including price-based bid construction and price revising mechanism. We propose a simulation-based iteration procedure in order to revise the decision making parameters. It is shown that the iterative procedure eventually improves the global performance of the entire system. The proposed method is expected to have flexibility against various system alternations, addition or deletion of jobs or sudden failure of machines. We develop a prototype software that utilizes the object oriented concept. 
2. Abstract of Cited Paper (BIB002):  In this paper, a mixed integer programming model is formulated for scheduling a set of jobs through a shop when each job is supplied or provided with multiple process plans or process routings. Simultaneous selection of a process plan for each job and the sequencing of the jobs through the machines in the shop based on the set of selected process plans is addressed. The procedure developed seeks to integrate the selection of machines for each job and the sequencing of jobs on each machine based on the objective of minimizing production makespan. the application of the procedure is demonstrated with an example problem. The following conclusions were drawn as a result of the research: (1) the procedure developed produces optimal or near optimal solution; (2) the benefit from the developed approach is that it allows a shop to adaptively select process plans for jobs to optimize on production makespan. By combining solution quality with scheduling flexibility and efficiency, the productivity of a shop can be ... 
3. Abstract of Cited Paper (BIB003):  Traditional job shop scheduling problems generally assume that there is a single feasible routing with which a part can be processed in a shop. In today's flexible production systems, this assumption is rarely true. For most manufactured parts, it is possible to generate multiple ways to sequence the operations required to realize the finished product. Each feasible ordering of the operations generates a process plan. Multiple process plans per job increase production flexibility, while at the same time they increase planning and scheduling difficulty. In this paper, the problem of scheduling multiple jobs with each having multiple process plans in a job shop environment is addressed. The problem is modelled and solved using a mathematical approach. Because of the high computational effort required to solve the model using an exact solution procedure, two algorithms were developed and compared against solutions obtained by an optimum finding technique. The results of the test problems indicate that one of... 
4. Abstract of Cited Paper (BIB004):  This paper highlights the importance of integration between process planning and scheduling in flexible manufacturing systems (FMS). An effective integration increases the potential for enhanced system performance and enhanced decision making. A framework that integrates flexible process plans with off-line (predictive) scheduling in FMS is presented. The flexibility in process planning, including process flexibility, sequence flexibility, and alternative machine tools, is discussed. The proposed framework consists of four integrated stages with the objective of reducing the completion time. The integrated stages include. 1. Machine tool sclection. 2. Process plan selection. 3. Scheduling. 4. Re-scheduling modules. In addition, the paper proposes a new approach, namely the Dissimilarity Maximisation Method (DMM). for selecting the appropriate process plans for a part mix where parts have alternative process plans. The recursive structure of the framework provides a different approach, namely overlapping schedules, which considers a longer scheduling period as comprising several short scheduling periods. Knowing that neither the process plans nor the planned (predicted) schedules are truly followed on the shop floor, the related literature and the corresponding approaches are compared in order to envisage new approaches for closing the gap between process planning and scheduling. 
5. Abstract of Cited Paper (BIB005):  Abstract Successful implementation of automated manufacturing systems highly depends on effective utilization of resources. Efficient scheduling algorithms for alternative process plans may increase the throughput rate and guarantee a reasonable return on investment. This paper investigates an optimization methodology for scheduling jobs in a just-in-time environment. We consider the non-preemptive case where each job consists of a distinct number of operations to be processed in a specified order. Each operation has to be processed on one of a set of resources (e.g. machines) with possibly different efficiency and hence processing time. The objective is to minimize the sum of the weighted quadratic tardiness of the jobs. We obtain a fast near-optimal algorithm with guaranteed bounds for the distance to the optimum by using Lagrangian relaxation and show that just one relaxation suffices. 
6. Abstract of Cited Paper (BIB006):  The primary objective of this research was to develop a prototype feature-based multiple-alternative process planning system in which the process plan would be generated directly from design and available factory facility information. An overall removable volume is generated by graphically comparing the 3D part and 3D workpiece blank. The manufacturing features are decomposed into a series of general manufacturing features by using a mixed graph-based and rule-based algorithm. The multiple-alternative process plan generation is based on recognized manufacturing features and various production rules. After generating multiple process plans, each process plan is allocated the possible manufacturing scheduling time and the candidate process plans are retrieved based on the required due day. An example problem is presented to illustrate the functionality of the prototype system. This research presents an alternative method that provides useful information to the factory planner and controller to facilitate production. 
7. Abstract of Cited Paper (BIB007):  This paper addresses the integrated problem of process planning and scheduling in job shop flexible manufacturing systems. Due to production flexibility, it is possible to generate many feasible process plans for each job. The two functions of process planning and scheduling are tightly interwoven with each other. The optimality of scheduling depends on the result of process planning. The integration of process planning and scheduling is therefore important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. For the performance improvement of the algorithm, it is important to enhance population diversity and search efficiency. We adopt the strategies of localized interactions, steady-state reproduction, and random symbiotic partner selection. Efficient genetic representations and operator schemes are also considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and an existing cooperative coevolutionary algorithm. The experimental results show that the proposed algorithm outperforms the compared algorithms. 
8. Abstract of Cited Paper (BIB008):  Abstract In this paper we study an extension of the job-shop scheduling problem where the job routings are directed acyclic graphs that can model partial orders of operations and that contain sets of alternative subgraphs consisting of several operations each. We develop two heuristic algorithms for our problem: a tabu search and a genetic algorithm. The two heuristics are based on two common subroutines: one to insert a set of operations into a partial schedule and another to improve a schedule with fixed routing alternatives. The first subroutine relies on an efficient operation insertion technique and the second one is a generalisation of standard methods for classical job-shop scheduling. We compare our heuristics on various test problems, including the special case MPM job-shop scheduling. Moreover, we report on the success of the two subroutines on open-shop instances. 
9. Abstract of Cited Paper (BIB009):  In recent years, process planners have become interested in the development of dynamic process planning systems that can interface to scheduling systems providing alternative process plans to increase flexibility in scheduling. However, deciding how many alternatives are needed has not been addressed in any previous studies. This paper presents the results of a simulation-based study aimed at characterizing the benefit provided from having alternative plans available for use in scheduling. This benefit is quantified in terms of the overall performance of a job-shop manufacturing environment. The results of this study indicate that the advantage gained by increasing the number of alternative process plans diminishes rapidly. In fact, under some conditions for the particular system studied, increasing the number of alternatives actually resulted in degraded system performance. Based on these results developers of process planning systems and methodologies need to evaluate carefully the benefit of expending time and resources on the generation of alternative plans or optimal plans. 
10. Abstract of Cited Paper (BIB010):  Process planning and scheduling are the two important manufacturing functions involved in any shop floor activities. As functional integration is essential to realize the benefits of computer integrated manufacturing, a scheme for integration of process planning and scheduling has been introduced in this paper. The proposed scheme can be implemented in a company with existing process planning and scheduling departments when multiple process plans remain available on the shop floor. It consists of two main modules, introduced in detail in this paper. They are process plan selection module and scheduling module. 
11. Abstract of Cited Paper (BIB011):  A job shop needs to deal with a lot of make-to-order business, in which the orders are usually diverse in types but each one is small in volume. To increase the flexibility and responsiveness of the job shop in the more competitive market, process planning and scheduling modules have been actively developed and deployed. The functions of the two modules are usually complementary. It is ideal to integrate them more tightly to achieve the global optimization of product development and manufacturing. In this paper, a unified representation model and a simulated annealing-based approach have been developed to facilitate the integration and optimization process. In the approach, three strategies, including processing flexibility, operation sequencing flexibility and scheduling flexibility, have been used for exploring the search space to support the optimization process effectively. Performance criteria, such as makespan, the balanced level of machine utilization, job tardiness and manufacturing cost, have been systematically defined to make the algorithm adaptive to meet various practical requirements. Case studies under various working conditions and the comparisons of this approach with two modern evolutionary approaches are given. The merits and characteristics of the approach are thereby highlighted. 
12. Abstract of Cited Paper (BIB012):  Traditionally, process planning and scheduling for parts were carried out in a sequential way, where scheduling was done after process plans had been generated. Considering the fact that the two functions are usually complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved greatly. In this paper, a new integration model and a modified genetic algorithm-based approach have been developed to facilitate the integration and optimization of the two functions. In the model, process planning and scheduling functions are carried out simultaneously. In order to improve the optimized performance of the modified genetic algorithm-based approach, more efficient genetic representations and operator schemes have been developed. Experimental studies have been conducted and the comparisons have been made between this approach and others to indicate the superiority and adaptability of this method. The experimental results show that the proposed approach is a promising and very effective method for the integration of process planning and scheduling.

Literature Review:
The methodology of NLPP is to make all alternative process plans for each part with a rank according to process-planning optimisation criteria. The plan with highest priority is always ready for submission when the job is required. If the first-priority plan is not suitable for the current shop floor status, the second-priority plan will be provided to the scheduling system. NLPP can also be called as flexible process-planning, multi-process planning or alternative process planning. The basic flow chart of NLPP is shown in Figure 1 . On the basis of the basic flow chart of NLPP, the process planning system and scheduling system are separate. NLPP only uses alternative process plans to enhance the flexibility of the manufacturing system. NLPP is the most basic model of IPPS. Because the integration methodology of this model is very simple, most of the current research works on the integration model focus on the improvement and implementation of this model. BIB001 described the concept and prototype implementation of a flexible integrated production planning and scheduling system. BIB002 gave a scheduling system, which was supported by flexible process plans and based on negotiation. BIB003 formulated a mixed-integer programming model for job shop scheduling with multiple process plans. BIB004 developed a mixed-integer programming model for job shop scheduling with multiple process plans, and proposed two algorithms to solve this problem. BIB005 presented a framework that integrated flexible process plans with off-line scheduling in flexible manufacturing system. And, it also proposed an approach, namely the dissimilarity maximisation method, for selecting the appropriate process plans for a part mix where parts had alternative process plans.  presented the NLPP model based on the GA. BIB006 investigated an optimisation methodology for scheduling jobs with alternative process plans in a just-in-time environment. BIB007 presented a prototype of a feature-based multiple alternative process planning system. Gan and Lee (2002) described a process-planning and scheduling system that makes use of the branch and bound approach to optimise priority weighted earliness of jobs scheduled in a mould manufacturing shop. BIB008 used a symbiotic evolutionary algorithm for IPPS. BIB009 developed two heuristic algorithms for the JSP with alternative process plans: a TS and a GA. BIB011 proposed a scheme for IPPS that could be implemented in a company with existing process planning and scheduling departments when multiple process plans for each part type were available. BIB012 used an SA-based approach for IPPS. BIB013 used a modified GA to solve this problem. However, through a number of experimental computations, BIB010 concluded that the advantages gained by increasing the number of alternative process plans for a scheduling system diminishes rapidly when the number of the plans reaches a certain level. The computational efficiency needs to be improved when applying to a complex system with a large number of alternative solutions.